mirror of
https://github.com/mmaithani/data-science.git
synced 2022-04-24 02:56:41 +03:00
1921 lines
123 KiB
Plaintext
1921 lines
123 KiB
Plaintext
{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"name": "OneNet.ipynb",
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"provenance": [],
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"collapsed_sections": [],
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"machine_shape": "hm",
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"include_colab_link": true
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/mmaithani/data-science/blob/main/OneNet.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "afXzzm_jWM39",
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"outputId": "7c978d0a-01f7-4725-be26-e55f78286cf8"
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},
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"source": [
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"!git clone https://github.com/PeizeSun/OneNet.git"
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],
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"execution_count": 1,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"Cloning into 'OneNet'...\n",
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"remote: Enumerating objects: 557, done.\u001b[K\n",
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"remote: Counting objects: 100% (557/557), done.\u001b[K\n",
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"remote: Compressing objects: 100% (470/470), done.\u001b[K\n",
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"remote: Total 557 (delta 114), reused 479 (delta 77), pack-reused 0\u001b[K\n",
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"Receiving objects: 100% (557/557), 1.48 MiB | 10.97 MiB/s, done.\n",
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"Resolving deltas: 100% (114/114), done.\n"
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],
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"name": "stdout"
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}
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "6ArB46hUXgNC",
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"outputId": "0e40b04f-564d-4c5e-8923-b4f666f774df"
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},
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"source": [
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"cd OneNet"
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],
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"execution_count": 3,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"/content/OneNet\n"
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],
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"name": "stdout"
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}
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "CxGYhfl3rCy4"
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},
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"source": [
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"# installing torchvison according to your cuda version"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "ora4M9KThIwk",
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"outputId": "9308617f-3086-451a-906a-188577256692"
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},
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"source": [
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"!nvcc --version"
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],
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"execution_count": 9,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"nvcc: NVIDIA (R) Cuda compiler driver\n",
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"Copyright (c) 2005-2019 NVIDIA Corporation\n",
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"Built on Sun_Jul_28_19:07:16_PDT_2019\n",
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"Cuda compilation tools, release 10.1, V10.1.243\n"
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],
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"name": "stdout"
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}
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 462
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},
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"id": "aLOtDDDihcy0",
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"outputId": "14d35671-6a99-49e5-afff-cbd95fd37e9e"
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},
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"source": [
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"pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio===0.7.2 -f https://download.pytorch.org/whl/torch_stable.html"
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],
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"execution_count": 10,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"Looking in links: https://download.pytorch.org/whl/torch_stable.html\n",
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"Collecting torch==1.7.1+cu101\n",
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"\u001b[?25l Downloading https://download.pytorch.org/whl/cu101/torch-1.7.1%2Bcu101-cp36-cp36m-linux_x86_64.whl (735.4MB)\n",
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"\u001b[K |████████████████████████████████| 735.4MB 23kB/s \n",
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"\u001b[?25hCollecting torchvision==0.8.2+cu101\n",
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"\u001b[?25l Downloading https://download.pytorch.org/whl/cu101/torchvision-0.8.2%2Bcu101-cp36-cp36m-linux_x86_64.whl (12.8MB)\n",
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"\u001b[K |████████████████████████████████| 12.8MB 14kB/s \n",
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"\u001b[?25hRequirement already satisfied: torchaudio===0.7.2 in /usr/local/lib/python3.6/dist-packages (0.7.2)\n",
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"Requirement already satisfied: dataclasses; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from torch==1.7.1+cu101) (0.8)\n",
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"Requirement already satisfied: typing-extensions in /usr/local/lib/python3.6/dist-packages (from torch==1.7.1+cu101) (3.7.4.3)\n",
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"Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from torch==1.7.1+cu101) (1.18.5)\n",
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"Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.6/dist-packages (from torchvision==0.8.2+cu101) (7.0.0)\n",
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"Installing collected packages: torch, torchvision\n",
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" Found existing installation: torch 1.7.1+cu110\n",
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" Uninstalling torch-1.7.1+cu110:\n",
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" Successfully uninstalled torch-1.7.1+cu110\n",
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" Found existing installation: torchvision 0.8.2+cu110\n",
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" Uninstalling torchvision-0.8.2+cu110:\n",
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" Successfully uninstalled torchvision-0.8.2+cu110\n",
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"Successfully installed torch-1.7.1+cu101 torchvision-0.8.2+cu101\n"
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],
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"name": "stdout"
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},
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{
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"output_type": "display_data",
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"data": {
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"application/vnd.colab-display-data+json": {
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"pip_warning": {
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"packages": [
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"torch",
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"torchvision"
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]
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}
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}
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},
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"metadata": {
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"tags": []
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}
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}
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "PwA0CZNlaxXg"
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},
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"source": [
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"# restart runtime after installing"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "SATmJGGiad0Q"
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},
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"source": [
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"!pip install pyyaml==5.1 pycocotools>=2.0.1"
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],
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"execution_count": 4,
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"outputs": []
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "f5-hLPy_Zg9p"
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},
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"source": [
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"import torch, torchvision\r\n",
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"print(torch.__version__, torch.cuda.is_available())"
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],
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "IRMp5PH0ZaTQ"
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},
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"source": [
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"# install onenet"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "VEOfkYVsW6ck",
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"outputId": "62b3f2bb-32a0-423d-c350-59344fe60b07"
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},
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"source": [
|
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"!python setup.py build develop"
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],
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"execution_count": 6,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"/usr/local/lib/python3.6/dist-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: The NVIDIA driver on your system is too old (found version 10010). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at /pytorch/c10/cuda/CUDAFunctions.cpp:100.)\n",
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" return torch._C._cuda_getDeviceCount() > 0\n",
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"No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'\n",
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"running build\n",
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"running build_py\n",
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"creating build\n",
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"creating build/lib.linux-x86_64-3.6\n",
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"creating build/lib.linux-x86_64-3.6/detectron2\n",
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"copying detectron2/__init__.py -> build/lib.linux-x86_64-3.6/detectron2\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/data\n",
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"copying detectron2/data/detection_utils.py -> build/lib.linux-x86_64-3.6/detectron2/data\n",
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"copying detectron2/data/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/data\n",
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"copying detectron2/data/dataset_mapper.py -> build/lib.linux-x86_64-3.6/detectron2/data\n",
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"copying detectron2/data/common.py -> build/lib.linux-x86_64-3.6/detectron2/data\n",
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"copying detectron2/data/catalog.py -> build/lib.linux-x86_64-3.6/detectron2/data\n",
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"copying detectron2/data/build.py -> build/lib.linux-x86_64-3.6/detectron2/data\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/logger.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/collect_env.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/comm.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/registry.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/serialize.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/memory.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/testing.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/env.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/colormap.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/video_visualizer.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/events.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/analysis.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/visualizer.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"copying detectron2/utils/file_io.py -> build/lib.linux-x86_64-3.6/detectron2/utils\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"copying detectron2/modeling/postprocessing.py -> build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"copying detectron2/modeling/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"copying detectron2/modeling/test_time_augmentation.py -> build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"copying detectron2/modeling/sampling.py -> build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"copying detectron2/modeling/poolers.py -> build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"copying detectron2/modeling/matcher.py -> build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"copying detectron2/modeling/box_regression.py -> build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"copying detectron2/modeling/anchor_generator.py -> build/lib.linux-x86_64-3.6/detectron2/modeling\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo\n",
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"copying detectron2/model_zoo/model_zoo.py -> build/lib.linux-x86_64-3.6/detectron2/model_zoo\n",
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"copying detectron2/model_zoo/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/model_zoo\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/engine\n",
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"copying detectron2/engine/launch.py -> build/lib.linux-x86_64-3.6/detectron2/engine\n",
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"copying detectron2/engine/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/engine\n",
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"copying detectron2/engine/hooks.py -> build/lib.linux-x86_64-3.6/detectron2/engine\n",
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"copying detectron2/engine/defaults.py -> build/lib.linux-x86_64-3.6/detectron2/engine\n",
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"copying detectron2/engine/train_loop.py -> build/lib.linux-x86_64-3.6/detectron2/engine\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/checkpoint\n",
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"copying detectron2/checkpoint/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/checkpoint\n",
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"copying detectron2/checkpoint/detection_checkpoint.py -> build/lib.linux-x86_64-3.6/detectron2/checkpoint\n",
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"copying detectron2/checkpoint/catalog.py -> build/lib.linux-x86_64-3.6/detectron2/checkpoint\n",
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"copying detectron2/checkpoint/c2_model_loading.py -> build/lib.linux-x86_64-3.6/detectron2/checkpoint\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/structures\n",
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"copying detectron2/structures/image_list.py -> build/lib.linux-x86_64-3.6/detectron2/structures\n",
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"copying detectron2/structures/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/structures\n",
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"copying detectron2/structures/boxes.py -> build/lib.linux-x86_64-3.6/detectron2/structures\n",
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"copying detectron2/structures/instances.py -> build/lib.linux-x86_64-3.6/detectron2/structures\n",
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"copying detectron2/structures/keypoints.py -> build/lib.linux-x86_64-3.6/detectron2/structures\n",
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"copying detectron2/structures/rotated_boxes.py -> build/lib.linux-x86_64-3.6/detectron2/structures\n",
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"copying detectron2/structures/masks.py -> build/lib.linux-x86_64-3.6/detectron2/structures\n",
|
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"creating build/lib.linux-x86_64-3.6/detectron2/export\n",
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"copying detectron2/export/api.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
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"copying detectron2/export/shared.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
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"copying detectron2/export/caffe2_patch.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
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"copying detectron2/export/caffe2_inference.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
|
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"copying detectron2/export/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
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"copying detectron2/export/torchscript.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
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"copying detectron2/export/torchscript_patch.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
|
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"copying detectron2/export/caffe2_export.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
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"copying detectron2/export/c10.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
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"copying detectron2/export/caffe2_modeling.py -> build/lib.linux-x86_64-3.6/detectron2/export\n",
|
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"creating build/lib.linux-x86_64-3.6/detectron2/config\n",
|
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"copying detectron2/config/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/config\n",
|
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"copying detectron2/config/config.py -> build/lib.linux-x86_64-3.6/detectron2/config\n",
|
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"copying detectron2/config/defaults.py -> build/lib.linux-x86_64-3.6/detectron2/config\n",
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"copying detectron2/config/compat.py -> build/lib.linux-x86_64-3.6/detectron2/config\n",
|
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"creating build/lib.linux-x86_64-3.6/detectron2/projects\n",
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"copying detectron2/projects/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/projects\n",
|
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"creating build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/rotated_coco_evaluation.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/pascal_voc_evaluation.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/testing.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/evaluator.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/fast_eval_api.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/sem_seg_evaluation.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/coco_evaluation.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/cityscapes_evaluation.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/panoptic_evaluation.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"copying detectron2/evaluation/lvis_evaluation.py -> build/lib.linux-x86_64-3.6/detectron2/evaluation\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/layers\n",
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"copying detectron2/layers/roi_align.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
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"copying detectron2/layers/mask_ops.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
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"copying detectron2/layers/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
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"copying detectron2/layers/batch_norm.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
|
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"copying detectron2/layers/wrappers.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
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"copying detectron2/layers/aspp.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
|
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"copying detectron2/layers/shape_spec.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
|
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"copying detectron2/layers/deform_conv.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
|
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"copying detectron2/layers/blocks.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
|
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"copying detectron2/layers/roi_align_rotated.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
|
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"copying detectron2/layers/rotated_boxes.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
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"copying detectron2/layers/nms.py -> build/lib.linux-x86_64-3.6/detectron2/layers\n",
|
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"creating build/lib.linux-x86_64-3.6/detectron2/solver\n",
|
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"copying detectron2/solver/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/solver\n",
|
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"copying detectron2/solver/lr_scheduler.py -> build/lib.linux-x86_64-3.6/detectron2/solver\n",
|
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"copying detectron2/solver/build.py -> build/lib.linux-x86_64-3.6/detectron2/solver\n",
|
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"creating build/lib.linux-x86_64-3.6/detectron2/data/samplers\n",
|
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"copying detectron2/data/samplers/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/data/samplers\n",
|
|
"copying detectron2/data/samplers/grouped_batch_sampler.py -> build/lib.linux-x86_64-3.6/detectron2/data/samplers\n",
|
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"copying detectron2/data/samplers/distributed_sampler.py -> build/lib.linux-x86_64-3.6/detectron2/data/samplers\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/data/transforms\n",
|
|
"copying detectron2/data/transforms/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/data/transforms\n",
|
|
"copying detectron2/data/transforms/augmentation.py -> build/lib.linux-x86_64-3.6/detectron2/data/transforms\n",
|
|
"copying detectron2/data/transforms/transform.py -> build/lib.linux-x86_64-3.6/detectron2/data/transforms\n",
|
|
"copying detectron2/data/transforms/augmentation_impl.py -> build/lib.linux-x86_64-3.6/detectron2/data/transforms\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/lvis_v1_categories.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/builtin_meta.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/pascal_voc.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/lvis.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/cityscapes.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/builtin.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/cityscapes_panoptic.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/coco_panoptic.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/coco.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/lvis_v0_5_categories.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"copying detectron2/data/datasets/register_coco.py -> build/lib.linux-x86_64-3.6/detectron2/data/datasets\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"copying detectron2/modeling/roi_heads/fast_rcnn.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"copying detectron2/modeling/roi_heads/keypoint_head.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"copying detectron2/modeling/roi_heads/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"copying detectron2/modeling/roi_heads/cascade_rcnn.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"copying detectron2/modeling/roi_heads/mask_head.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"copying detectron2/modeling/roi_heads/rotated_fast_rcnn.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"copying detectron2/modeling/roi_heads/roi_heads.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"copying detectron2/modeling/roi_heads/box_head.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/roi_heads\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/modeling/meta_arch\n",
|
|
"copying detectron2/modeling/meta_arch/panoptic_fpn.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/meta_arch\n",
|
|
"copying detectron2/modeling/meta_arch/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/meta_arch\n",
|
|
"copying detectron2/modeling/meta_arch/semantic_seg.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/meta_arch\n",
|
|
"copying detectron2/modeling/meta_arch/rcnn.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/meta_arch\n",
|
|
"copying detectron2/modeling/meta_arch/retinanet.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/meta_arch\n",
|
|
"copying detectron2/modeling/meta_arch/build.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/meta_arch\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/modeling/proposal_generator\n",
|
|
"copying detectron2/modeling/proposal_generator/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/proposal_generator\n",
|
|
"copying detectron2/modeling/proposal_generator/proposal_utils.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/proposal_generator\n",
|
|
"copying detectron2/modeling/proposal_generator/rrpn.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/proposal_generator\n",
|
|
"copying detectron2/modeling/proposal_generator/rpn.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/proposal_generator\n",
|
|
"copying detectron2/modeling/proposal_generator/build.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/proposal_generator\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/modeling/backbone\n",
|
|
"copying detectron2/modeling/backbone/fpn.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/backbone\n",
|
|
"copying detectron2/modeling/backbone/backbone.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/backbone\n",
|
|
"copying detectron2/modeling/backbone/__init__.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/backbone\n",
|
|
"copying detectron2/modeling/backbone/build.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/backbone\n",
|
|
"copying detectron2/modeling/backbone/resnet.py -> build/lib.linux-x86_64-3.6/detectron2/modeling/backbone\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs\n",
|
|
"copying detectron2/model_zoo/configs/Base-RCNN-DilatedC5.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs\n",
|
|
"copying detectron2/model_zoo/configs/Base-RCNN-C4.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs\n",
|
|
"copying detectron2/model_zoo/configs/Base-RetinaNet.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs\n",
|
|
"copying detectron2/model_zoo/configs/Base-RCNN-FPN.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_DC5_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_101_C4_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/rpn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/rpn_R_50_C4_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/retinanet_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/retinanet_R_101_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_101_DC5_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_DC5_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_X_101_32x8d_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_C4_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_50_C4_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/retinanet_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/fast_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/faster_rcnn_R_101_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection/zhang\n",
|
|
"copying detectron2/model_zoo/configs/COCO-Detection/zhang/faster_rcnn_R_50_C4_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Detection/zhang\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/LVISv1-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/LVISv1-InstanceSegmentation/mask_rcnn_X_101_32x8d_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/LVISv1-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/LVISv1-InstanceSegmentation/mask_rcnn_R_101_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/LVISv1-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/LVISv1-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/LVISv1-InstanceSegmentation\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_C4_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_101_DC5_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_DC5_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_DC5_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_101_C4_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_C4_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_X_101_32x8d_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"copying detectron2/model_zoo/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_1x_giou.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-InstanceSegmentation\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/cascade_mask_rcnn_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_3x_gn.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/scratch_mask_rcnn_R_50_FPN_9x_gn.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/scratch_mask_rcnn_R_50_FPN_3x_gn.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/semantic_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_1x_dconv_c3-c5.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_3x_dconv_c3-c5.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_1x_cls_agnostic.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/panoptic_fpn_R_101_dconv_cascade_gn_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/cascade_mask_rcnn_X_152_32x8d_FPN_IN5k_gn_dconv.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/mask_rcnn_R_50_FPN_3x_syncbn.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/cascade_mask_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"copying detectron2/model_zoo/configs/Misc/scratch_mask_rcnn_R_50_FPN_9x_syncbn.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Misc\n",
|
|
"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
|
|
"copying detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
|
|
"copying detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_training_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
|
|
"copying detectron2/model_zoo/configs/quick_schedules/rpn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
|
|
"copying detectron2/model_zoo/configs/quick_schedules/fast_rcnn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
|
|
"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
|
|
"copying detectron2/model_zoo/configs/quick_schedules/retinanet_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/semantic_R_50_FPN_training_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_training_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/retinanet_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/cascade_mask_rcnn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/semantic_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/rpn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/semantic_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_normalized_training_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_pred_boxes_training_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/cascade_mask_rcnn_R_50_FPN_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_GCV_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_training_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_DC5_inference_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_training_acc_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"copying detectron2/model_zoo/configs/quick_schedules/fast_rcnn_R_50_FPN_instant_test.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/quick_schedules\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
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"copying detectron2/model_zoo/configs/COCO-PanopticSegmentation/panoptic_fpn_R_50_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
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"copying detectron2/model_zoo/configs/COCO-PanopticSegmentation/panoptic_fpn_R_50_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
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"copying detectron2/model_zoo/configs/COCO-PanopticSegmentation/panoptic_fpn_R_101_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
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"copying detectron2/model_zoo/configs/COCO-PanopticSegmentation/Base-Panoptic-FPN.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-PanopticSegmentation\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Detectron1-Comparisons\n",
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"copying detectron2/model_zoo/configs/Detectron1-Comparisons/keypoint_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Detectron1-Comparisons\n",
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"copying detectron2/model_zoo/configs/Detectron1-Comparisons/mask_rcnn_R_50_FPN_noaug_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Detectron1-Comparisons\n",
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"copying detectron2/model_zoo/configs/Detectron1-Comparisons/faster_rcnn_R_50_FPN_noaug_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Detectron1-Comparisons\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Keypoints\n",
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"copying detectron2/model_zoo/configs/COCO-Keypoints/keypoint_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Keypoints\n",
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"copying detectron2/model_zoo/configs/COCO-Keypoints/keypoint_rcnn_X_101_32x8d_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Keypoints\n",
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"copying detectron2/model_zoo/configs/COCO-Keypoints/keypoint_rcnn_R_50_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Keypoints\n",
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"copying detectron2/model_zoo/configs/COCO-Keypoints/Base-Keypoint-RCNN-FPN.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Keypoints\n",
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"copying detectron2/model_zoo/configs/COCO-Keypoints/keypoint_rcnn_R_101_FPN_3x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/COCO-Keypoints\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation\n",
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"copying detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation/mask_rcnn_X_101_32x8d_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation\n",
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"copying detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation/mask_rcnn_R_101_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation\n",
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"copying detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/LVISv0.5-InstanceSegmentation\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Cityscapes\n",
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"copying detectron2/model_zoo/configs/Cityscapes/mask_rcnn_R_50_FPN.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/Cityscapes\n",
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"creating build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/PascalVOC-Detection\n",
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"copying detectron2/model_zoo/configs/PascalVOC-Detection/faster_rcnn_R_50_C4.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/PascalVOC-Detection\n",
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"copying detectron2/model_zoo/configs/PascalVOC-Detection/faster_rcnn_R_50_FPN.yaml -> build/lib.linux-x86_64-3.6/detectron2/model_zoo/configs/PascalVOC-Detection\n",
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"running build_ext\n",
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"/usr/local/lib/python3.6/dist-packages/torch/utils/cpp_extension.py:352: UserWarning: Attempted to use ninja as the BuildExtension backend but we could not find ninja.. Falling back to using the slow distutils backend.\n",
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" warnings.warn(msg.format('we could not find ninja.'))\n",
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"building 'detectron2._C' extension\n",
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"creating build/temp.linux-x86_64-3.6\n",
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"creating build/temp.linux-x86_64-3.6/content\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet/detectron2\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/ROIAlignRotated\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/box_iou_rotated\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/cocoeval\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/ROIAlign\n",
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"creating build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/nms_rotated\n",
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"x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/include/python3.6m -c /content/OneNet/detectron2/layers/csrc/vision.cpp -o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/vision.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
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"In file included from \u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/Parallel.h:149:0\u001b[m\u001b[K,\n",
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" from \u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include/torch/utils.h:3\u001b[m\u001b[K,\n",
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" from \u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:5\u001b[m\u001b[K,\n",
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" from \u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include/torch/nn.h:3\u001b[m\u001b[K,\n",
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" from \u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:12\u001b[m\u001b[K,\n",
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" from \u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
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" from \u001b[01m\u001b[K/content/OneNet/detectron2/layers/csrc/vision.cpp:3\u001b[m\u001b[K:\n",
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"\u001b[01m\u001b[K/usr/local/lib/python3.6/dist-packages/torch/include/ATen/ParallelOpenMP.h:84:0:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kignoring #pragma omp parallel [\u001b[01;35m\u001b[K-Wunknown-pragmas\u001b[m\u001b[K]\n",
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" #pragma omp parallel for if ((end - begin) >= grain_size)\n",
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" \n",
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"x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/include/python3.6m -c /content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cpu.cpp -o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
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"x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/include/python3.6m -c /content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cpu.cpp -o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
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"x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/include/python3.6m -c /content/OneNet/detectron2/layers/csrc/cocoeval/cocoeval.cpp -o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/cocoeval/cocoeval.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
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"x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/include/python3.6m -c /content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cpu.cpp -o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
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"x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/content/OneNet/detectron2/layers/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/include/python3.6m -c /content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cpu.cpp -o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14\n",
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"x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/vision.o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cpu.o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cpu.o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/cocoeval/cocoeval.o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/ROIAlign/ROIAlign_cpu.o build/temp.linux-x86_64-3.6/content/OneNet/detectron2/layers/csrc/nms_rotated/nms_rotated_cpu.o -L/usr/local/lib/python3.6/dist-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-3.6/detectron2/_C.cpython-36m-x86_64-linux-gnu.so\n",
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"running develop\n",
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"running egg_info\n",
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"creating detectron2.egg-info\n",
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"writing detectron2.egg-info/PKG-INFO\n",
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"writing dependency_links to detectron2.egg-info/dependency_links.txt\n",
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"writing requirements to detectron2.egg-info/requires.txt\n",
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"writing top-level names to detectron2.egg-info/top_level.txt\n",
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"writing manifest file 'detectron2.egg-info/SOURCES.txt'\n",
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"writing manifest file 'detectron2.egg-info/SOURCES.txt'\n",
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"running build_ext\n",
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"copying build/lib.linux-x86_64-3.6/detectron2/_C.cpython-36m-x86_64-linux-gnu.so -> detectron2\n",
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"Creating /usr/local/lib/python3.6/dist-packages/detectron2.egg-link (link to .)\n",
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"Adding detectron2 0.3 to easy-install.pth file\n",
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"\n",
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"Installed /content/OneNet\n",
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"Processing dependencies for detectron2==0.3\n",
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"Searching for fvcore>=0.1.1\n",
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"Reading https://pypi.org/simple/fvcore/\n",
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"Downloading https://files.pythonhosted.org/packages/12/4b/d83c447ecf44ae0b29a608b0e43ed267c9cdabf372644517833ed695a239/fvcore-0.1.2.post20201216.tar.gz#sha256=e99f521d6926dbe3888457e3be9867613849d651ce396cf4396c981968940adc\n",
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"Best match: fvcore 0.1.2.post20201216\n",
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"Processing fvcore-0.1.2.post20201216.tar.gz\n",
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"Writing /tmp/easy_install-0jqngdgh/fvcore-0.1.2.post20201216/setup.cfg\n",
|
|
"Running fvcore-0.1.2.post20201216/setup.py -q bdist_egg --dist-dir /tmp/easy_install-0jqngdgh/fvcore-0.1.2.post20201216/egg-dist-tmp-n1_nvums\n",
|
|
"zip_safe flag not set; analyzing archive contents...\n",
|
|
"Moving fvcore-0.1.2.post20201216-py3.6.egg to /usr/local/lib/python3.6/dist-packages\n",
|
|
"Adding fvcore 0.1.2.post20201216 to easy-install.pth file\n",
|
|
"\n",
|
|
"Installed /usr/local/lib/python3.6/dist-packages/fvcore-0.1.2.post20201216-py3.6.egg\n",
|
|
"Searching for mock\n",
|
|
"Reading https://pypi.org/simple/mock/\n",
|
|
"Downloading https://files.pythonhosted.org/packages/5c/03/b7e605db4a57c0f6fba744b11ef3ddf4ddebcada35022927a2b5fc623fdf/mock-4.0.3-py3-none-any.whl#sha256=122fcb64ee37cfad5b3f48d7a7d51875d7031aaf3d8be7c42e2bee25044eee62\n",
|
|
"Best match: mock 4.0.3\n",
|
|
"Processing mock-4.0.3-py3-none-any.whl\n",
|
|
"Installing mock-4.0.3-py3-none-any.whl to /usr/local/lib/python3.6/dist-packages\n",
|
|
"Adding mock 4.0.3 to easy-install.pth file\n",
|
|
"\n",
|
|
"Installed /usr/local/lib/python3.6/dist-packages/mock-4.0.3-py3.6.egg\n",
|
|
"Searching for yacs>=0.1.6\n",
|
|
"Reading https://pypi.org/simple/yacs/\n",
|
|
"Downloading https://files.pythonhosted.org/packages/38/4f/fe9a4d472aa867878ce3bb7efb16654c5d63672b86dc0e6e953a67018433/yacs-0.1.8-py3-none-any.whl#sha256=99f893e30497a4b66842821bac316386f7bd5c4f47ad35c9073ef089aa33af32\n",
|
|
"Best match: yacs 0.1.8\n",
|
|
"Processing yacs-0.1.8-py3-none-any.whl\n",
|
|
"Installing yacs-0.1.8-py3-none-any.whl to /usr/local/lib/python3.6/dist-packages\n",
|
|
"Adding yacs 0.1.8 to easy-install.pth file\n",
|
|
"\n",
|
|
"Installed /usr/local/lib/python3.6/dist-packages/yacs-0.1.8-py3.6.egg\n",
|
|
"Searching for pyyaml>=5.1\n",
|
|
"Reading https://pypi.org/simple/pyyaml/\n",
|
|
"Downloading https://files.pythonhosted.org/packages/64/c2/b80047c7ac2478f9501676c988a5411ed5572f35d1beff9cae07d321512c/PyYAML-5.3.1.tar.gz#sha256=b8eac752c5e14d3eca0e6dd9199cd627518cb5ec06add0de9d32baeee6fe645d\n",
|
|
"Best match: PyYAML 5.3.1\n",
|
|
"Processing PyYAML-5.3.1.tar.gz\n",
|
|
"Writing /tmp/easy_install-4q9ez2kp/PyYAML-5.3.1/setup.cfg\n",
|
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"Running PyYAML-5.3.1/setup.py -q bdist_egg --dist-dir /tmp/easy_install-4q9ez2kp/PyYAML-5.3.1/egg-dist-tmp-iqccoe3k\n",
|
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"In file included from \u001b[01m\u001b[Kext/_yaml.c:596:0\u001b[m\u001b[K:\n",
|
|
"\u001b[01m\u001b[Kext/_yaml.h:2:10:\u001b[m\u001b[K \u001b[01;31m\u001b[Kfatal error: \u001b[m\u001b[Kyaml.h: No such file or directory\n",
|
|
" #include \u001b[01;31m\u001b[K<yaml.h>\u001b[m\u001b[K\n",
|
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" \u001b[01;31m\u001b[K^~~~~~~~\u001b[m\u001b[K\n",
|
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"compilation terminated.\n",
|
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"Error compiling module, falling back to pure Python\n",
|
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"zip_safe flag not set; analyzing archive contents...\n",
|
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"Moving PyYAML-5.3.1-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n",
|
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"Adding PyYAML 5.3.1 to easy-install.pth file\n",
|
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"\n",
|
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"Installed /usr/local/lib/python3.6/dist-packages/PyYAML-5.3.1-py3.6-linux-x86_64.egg\n",
|
|
"Searching for pydot==1.3.0\n",
|
|
"Best match: pydot 1.3.0\n",
|
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"Adding pydot 1.3.0 to easy-install.pth file\n",
|
|
"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for future==0.16.0\n",
|
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"Best match: future 0.16.0\n",
|
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"Adding future 0.16.0 to easy-install.pth file\n",
|
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"Installing futurize script to /usr/local/bin\n",
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"Installing pasteurize script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for pycocotools==2.0.2\n",
|
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"Best match: pycocotools 2.0.2\n",
|
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"Adding pycocotools 2.0.2 to easy-install.pth file\n",
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for tensorboard==2.3.0\n",
|
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"Best match: tensorboard 2.3.0\n",
|
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"Adding tensorboard 2.3.0 to easy-install.pth file\n",
|
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"Installing tensorboard script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for tqdm==4.41.1\n",
|
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"Best match: tqdm 4.41.1\n",
|
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"Adding tqdm 4.41.1 to easy-install.pth file\n",
|
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"Installing tqdm script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for matplotlib==3.2.2\n",
|
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"Best match: matplotlib 3.2.2\n",
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"Adding matplotlib 3.2.2 to easy-install.pth file\n",
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for cloudpickle==1.3.0\n",
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"Best match: cloudpickle 1.3.0\n",
|
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"Adding cloudpickle 1.3.0 to easy-install.pth file\n",
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
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"Searching for tabulate==0.8.7\n",
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"Best match: tabulate 0.8.7\n",
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"Adding tabulate 0.8.7 to easy-install.pth file\n",
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"Installing tabulate script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for Pillow==7.0.0\n",
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"Best match: Pillow 7.0.0\n",
|
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"Adding Pillow 7.0.0 to easy-install.pth file\n",
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for termcolor==1.1.0\n",
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"Best match: termcolor 1.1.0\n",
|
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"Adding termcolor 1.1.0 to easy-install.pth file\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for pyparsing==2.4.7\n",
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"Best match: pyparsing 2.4.7\n",
|
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"Adding pyparsing 2.4.7 to easy-install.pth file\n",
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for Cython==0.29.21\n",
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"Best match: Cython 0.29.21\n",
|
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"Adding Cython 0.29.21 to easy-install.pth file\n",
|
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"Installing cygdb script to /usr/local/bin\n",
|
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"Installing cython script to /usr/local/bin\n",
|
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"Installing cythonize script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for setuptools==50.3.2\n",
|
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"Best match: setuptools 50.3.2\n",
|
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"Adding setuptools 50.3.2 to easy-install.pth file\n",
|
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"Installing easy_install script to /usr/local/bin\n",
|
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"Installing easy_install-3.8 script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for iopath==0.1.2\n",
|
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"Best match: iopath 0.1.2\n",
|
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"Adding iopath 0.1.2 to easy-install.pth file\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for numpy==1.18.5\n",
|
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"Best match: numpy 1.18.5\n",
|
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"Adding numpy 1.18.5 to easy-install.pth file\n",
|
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"Installing f2py script to /usr/local/bin\n",
|
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"Installing f2py3 script to /usr/local/bin\n",
|
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"Installing f2py3.6 script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for protobuf==3.12.4\n",
|
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"Best match: protobuf 3.12.4\n",
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"Adding protobuf 3.12.4 to easy-install.pth file\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for google-auth-oauthlib==0.4.2\n",
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"Best match: google-auth-oauthlib 0.4.2\n",
|
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"Adding google-auth-oauthlib 0.4.2 to easy-install.pth file\n",
|
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"Installing google-oauthlib-tool script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for absl-py==0.10.0\n",
|
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"Best match: absl-py 0.10.0\n",
|
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"Adding absl-py 0.10.0 to easy-install.pth file\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for wheel==0.36.1\n",
|
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"Best match: wheel 0.36.1\n",
|
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"Adding wheel 0.36.1 to easy-install.pth file\n",
|
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"Installing wheel script to /usr/local/bin\n",
|
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"\n",
|
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"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for Werkzeug==1.0.1\n",
|
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"Best match: Werkzeug 1.0.1\n",
|
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"Adding Werkzeug 1.0.1 to easy-install.pth file\n",
|
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"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
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"Searching for grpcio==1.34.0\n",
|
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"Best match: grpcio 1.34.0\n",
|
|
"Adding grpcio 1.34.0 to easy-install.pth file\n",
|
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"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for google-auth==1.17.2\n",
|
|
"Best match: google-auth 1.17.2\n",
|
|
"Adding google-auth 1.17.2 to easy-install.pth file\n",
|
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"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for tensorboard-plugin-wit==1.7.0\n",
|
|
"Best match: tensorboard-plugin-wit 1.7.0\n",
|
|
"Adding tensorboard-plugin-wit 1.7.0 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for requests==2.23.0\n",
|
|
"Best match: requests 2.23.0\n",
|
|
"Adding requests 2.23.0 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for six==1.15.0\n",
|
|
"Best match: six 1.15.0\n",
|
|
"Adding six 1.15.0 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for Markdown==3.3.3\n",
|
|
"Best match: Markdown 3.3.3\n",
|
|
"Adding Markdown 3.3.3 to easy-install.pth file\n",
|
|
"Installing markdown_py script to /usr/local/bin\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for kiwisolver==1.3.1\n",
|
|
"Best match: kiwisolver 1.3.1\n",
|
|
"Adding kiwisolver 1.3.1 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for python-dateutil==2.8.1\n",
|
|
"Best match: python-dateutil 2.8.1\n",
|
|
"Adding python-dateutil 2.8.1 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for cycler==0.10.0\n",
|
|
"Best match: cycler 0.10.0\n",
|
|
"Adding cycler 0.10.0 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for portalocker==2.0.0\n",
|
|
"Best match: portalocker 2.0.0\n",
|
|
"Adding portalocker 2.0.0 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for requests-oauthlib==1.3.0\n",
|
|
"Best match: requests-oauthlib 1.3.0\n",
|
|
"Adding requests-oauthlib 1.3.0 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for rsa==4.6\n",
|
|
"Best match: rsa 4.6\n",
|
|
"Adding rsa 4.6 to easy-install.pth file\n",
|
|
"Installing pyrsa-decrypt script to /usr/local/bin\n",
|
|
"Installing pyrsa-encrypt script to /usr/local/bin\n",
|
|
"Installing pyrsa-keygen script to /usr/local/bin\n",
|
|
"Installing pyrsa-priv2pub script to /usr/local/bin\n",
|
|
"Installing pyrsa-sign script to /usr/local/bin\n",
|
|
"Installing pyrsa-verify script to /usr/local/bin\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for pyasn1-modules==0.2.8\n",
|
|
"Best match: pyasn1-modules 0.2.8\n",
|
|
"Adding pyasn1-modules 0.2.8 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for cachetools==4.1.1\n",
|
|
"Best match: cachetools 4.1.1\n",
|
|
"Adding cachetools 4.1.1 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for certifi==2020.12.5\n",
|
|
"Best match: certifi 2020.12.5\n",
|
|
"Adding certifi 2020.12.5 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for chardet==3.0.4\n",
|
|
"Best match: chardet 3.0.4\n",
|
|
"Adding chardet 3.0.4 to easy-install.pth file\n",
|
|
"Installing chardetect script to /usr/local/bin\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for idna==2.10\n",
|
|
"Best match: idna 2.10\n",
|
|
"Adding idna 2.10 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for urllib3==1.24.3\n",
|
|
"Best match: urllib3 1.24.3\n",
|
|
"Adding urllib3 1.24.3 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for importlib-metadata==3.1.1\n",
|
|
"Best match: importlib-metadata 3.1.1\n",
|
|
"Adding importlib-metadata 3.1.1 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for oauthlib==3.1.0\n",
|
|
"Best match: oauthlib 3.1.0\n",
|
|
"Adding oauthlib 3.1.0 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for pyasn1==0.4.8\n",
|
|
"Best match: pyasn1 0.4.8\n",
|
|
"Adding pyasn1 0.4.8 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Searching for zipp==3.4.0\n",
|
|
"Best match: zipp 3.4.0\n",
|
|
"Adding zipp 3.4.0 to easy-install.pth file\n",
|
|
"\n",
|
|
"Using /usr/local/lib/python3.6/dist-packages\n",
|
|
"Finished processing dependencies for detectron2==0.3\n"
|
|
],
|
|
"name": "stdout"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "EZ4aOsnUqdeL"
|
|
},
|
|
"source": [
|
|
"# link coco datset to OneNet dateset folder\r\n",
|
|
"## download COCO dataset and then link the folder with OneNet"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"metadata": {
|
|
"id": "6TNWAF7bW_bN"
|
|
},
|
|
"source": [
|
|
"!mkdir -p datasets/coco\r\n",
|
|
"!ln -s /path_to_coco_dataset/annotations datasets/coco/annotations\r\n",
|
|
"!ln -s /path_to_coco_dataset/train2017 datasets/coco/train2017\r\n",
|
|
"!ln -s /path_to_coco_dataset/val2017 datasets/coco/val2017"
|
|
],
|
|
"execution_count": 8,
|
|
"outputs": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "01kNsDsFb0ry",
|
|
"outputId": "8298c36d-9816-4a9e-dc55-b84c194e451a"
|
|
},
|
|
"source": [
|
|
"pip install -U iopath"
|
|
],
|
|
"execution_count": 5,
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Collecting iopath\n",
|
|
" Downloading https://files.pythonhosted.org/packages/7a/9a/87a281c8cfc0ad1fceb228a4f854d02f19b2c2395476dd573327709b52ae/iopath-0.1.2.tar.gz\n",
|
|
"Requirement already satisfied, skipping upgrade: tqdm in /usr/local/lib/python3.6/dist-packages (from iopath) (4.41.1)\n",
|
|
"Collecting portalocker\n",
|
|
" Downloading https://files.pythonhosted.org/packages/89/a6/3814b7107e0788040870e8825eebf214d72166adf656ba7d4bf14759a06a/portalocker-2.0.0-py2.py3-none-any.whl\n",
|
|
"Building wheels for collected packages: iopath\n",
|
|
" Building wheel for iopath (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
|
|
" Created wheel for iopath: filename=iopath-0.1.2-cp36-none-any.whl size=10505 sha256=d04c9cd542839f205bcf4f00222b79b8e32104aa70ae256960a4ad8382689599\n",
|
|
" Stored in directory: /root/.cache/pip/wheels/9e/01/e4/1b68f5a2a6b9450ea4246d91840a77e1169f7d4722d76bbc47\n",
|
|
"Successfully built iopath\n",
|
|
"Installing collected packages: portalocker, iopath\n",
|
|
"Successfully installed iopath-0.1.2 portalocker-2.0.0\n"
|
|
],
|
|
"name": "stdout"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "qQOQZKS5rI3J"
|
|
},
|
|
"source": [
|
|
"# train ONeNet"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "T9_MTAAQXrIl",
|
|
"outputId": "20fd31f4-c7d1-4691-ea63-d595c6ab25f8"
|
|
},
|
|
"source": [
|
|
"!python projects/OneNet/train_net.py --num-gpus 1 \\\r\n",
|
|
" --config-file projects/OneNet/configs/onenet.res50.dcn.yaml"
|
|
],
|
|
"execution_count": 5,
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"text": [
|
|
"** fvcore version of PathManager will be deprecated soon. **\n",
|
|
"** Please migrate to the version in iopath repo. **\n",
|
|
"https://github.com/facebookresearch/iopath \n",
|
|
"\n",
|
|
"** fvcore version of PathManager will be deprecated soon. **\n",
|
|
"** Please migrate to the version in iopath repo. **\n",
|
|
"https://github.com/facebookresearch/iopath \n",
|
|
"\n",
|
|
"Command Line Args: Namespace(config_file='projects/OneNet/configs/onenet.res50.dcn.yaml', dist_url='tcp://127.0.0.1:49152', eval_only=False, machine_rank=0, num_gpus=1, num_machines=1, opts=[], resume=False)\n",
|
|
"\u001b[32m[12/17 11:48:48 detectron2]: \u001b[0mRank of current process: 0. World size: 1\n",
|
|
"cuobjdump info : File '/content/OneNet/detectron2/_C.cpython-36m-x86_64-linux-gnu.so' does not contain device code\n",
|
|
"\u001b[32m[12/17 11:48:48 detectron2]: \u001b[0mEnvironment info:\n",
|
|
"---------------------- ---------------------------------------------------------------\n",
|
|
"sys.platform linux\n",
|
|
"Python 3.6.9 (default, Oct 8 2020, 12:12:24) [GCC 8.4.0]\n",
|
|
"numpy 1.18.5\n",
|
|
"detectron2 0.3 @/content/OneNet/detectron2\n",
|
|
"Compiler GCC 7.5\n",
|
|
"CUDA compiler not available\n",
|
|
"detectron2 arch flags /content/OneNet/detectron2/_C.cpython-36m-x86_64-linux-gnu.so\n",
|
|
"DETECTRON2_ENV_MODULE <not set>\n",
|
|
"PyTorch 1.7.1+cu101 @/usr/local/lib/python3.6/dist-packages/torch\n",
|
|
"PyTorch debug build False\n",
|
|
"GPU available True\n",
|
|
"GPU 0 Tesla P100-PCIE-16GB (arch=6.0)\n",
|
|
"CUDA_HOME /usr/local/cuda\n",
|
|
"Pillow 7.0.0\n",
|
|
"torchvision 0.8.2+cu101 @/usr/local/lib/python3.6/dist-packages/torchvision\n",
|
|
"torchvision arch flags 3.5, 5.0, 6.0, 7.0, 7.5\n",
|
|
"fvcore 0.1.2.post20201216\n",
|
|
"cv2 4.1.2\n",
|
|
"---------------------- ---------------------------------------------------------------\n",
|
|
"PyTorch built with:\n",
|
|
" - GCC 7.3\n",
|
|
" - C++ Version: 201402\n",
|
|
" - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications\n",
|
|
" - Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)\n",
|
|
" - OpenMP 201511 (a.k.a. OpenMP 4.5)\n",
|
|
" - NNPACK is enabled\n",
|
|
" - CPU capability usage: AVX2\n",
|
|
" - CUDA Runtime 10.1\n",
|
|
" - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75\n",
|
|
" - CuDNN 7.6.3\n",
|
|
" - Magma 2.5.2\n",
|
|
" - Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, \n",
|
|
"\n",
|
|
"\u001b[32m[12/17 11:48:48 detectron2]: \u001b[0mCommand line arguments: Namespace(config_file='projects/OneNet/configs/onenet.res50.dcn.yaml', dist_url='tcp://127.0.0.1:49152', eval_only=False, machine_rank=0, num_gpus=1, num_machines=1, opts=[], resume=False)\n",
|
|
"\u001b[32m[12/17 11:48:48 detectron2]: \u001b[0mContents of args.config_file=projects/OneNet/configs/onenet.res50.dcn.yaml:\n",
|
|
"_BASE_: \"Base-OneNet.yaml\"\n",
|
|
"MODEL:\n",
|
|
" WEIGHTS: \"detectron2://ImageNetPretrained/torchvision/R-50.pkl\"\n",
|
|
" BACKBONE:\n",
|
|
" FREEZE_AT: 0\n",
|
|
" RESNETS:\n",
|
|
" NORM: \"BN\"\n",
|
|
" DEPTH: 50\n",
|
|
" STRIDE_IN_1X1: False\n",
|
|
" OneNet:\n",
|
|
" DCN: True\n",
|
|
" NUM_CLASSES: 80\n",
|
|
"DATASETS:\n",
|
|
" TRAIN: (\"coco_2017_train\",)\n",
|
|
" TEST: (\"coco_2017_val\",)\n",
|
|
"SOLVER:\n",
|
|
" IMS_PER_BATCH: 64\n",
|
|
" STEPS: (210000, 250000)\n",
|
|
" MAX_ITER: 270000\n",
|
|
"INPUT:\n",
|
|
" CROP:\n",
|
|
" ENABLED: True\n",
|
|
" FORMAT: \"RGB\"\n",
|
|
"OUTPUT_DIR: 'output_onenet_r50dcn'\n",
|
|
"\n",
|
|
"\u001b[32m[12/17 11:48:48 detectron2]: \u001b[0mRunning with full config:\n",
|
|
"CUDNN_BENCHMARK: False\n",
|
|
"DATALOADER:\n",
|
|
" ASPECT_RATIO_GROUPING: True\n",
|
|
" FILTER_EMPTY_ANNOTATIONS: False\n",
|
|
" NUM_WORKERS: 4\n",
|
|
" REPEAT_THRESHOLD: 0.0\n",
|
|
" SAMPLER_TRAIN: TrainingSampler\n",
|
|
"DATASETS:\n",
|
|
" PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000\n",
|
|
" PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000\n",
|
|
" PROPOSAL_FILES_TEST: ()\n",
|
|
" PROPOSAL_FILES_TRAIN: ()\n",
|
|
" TEST: ('coco_2017_val',)\n",
|
|
" TRAIN: ('coco_2017_train',)\n",
|
|
"GLOBAL:\n",
|
|
" HACK: 1.0\n",
|
|
"INPUT:\n",
|
|
" CROP:\n",
|
|
" ENABLED: True\n",
|
|
" SIZE: [384, 600]\n",
|
|
" TYPE: absolute_range\n",
|
|
" FORMAT: RGB\n",
|
|
" MASK_FORMAT: polygon\n",
|
|
" MAX_SIZE_TEST: 853\n",
|
|
" MAX_SIZE_TRAIN: 853\n",
|
|
" MIN_SIZE_TEST: 512\n",
|
|
" MIN_SIZE_TRAIN: (416, 448, 480, 512)\n",
|
|
" MIN_SIZE_TRAIN_SAMPLING: choice\n",
|
|
" RANDOM_FLIP: horizontal\n",
|
|
"MODEL:\n",
|
|
" ANCHOR_GENERATOR:\n",
|
|
" ANGLES: [[-90, 0, 90]]\n",
|
|
" ASPECT_RATIOS: [[0.5, 1.0, 2.0]]\n",
|
|
" NAME: DefaultAnchorGenerator\n",
|
|
" OFFSET: 0.0\n",
|
|
" SIZES: [[32, 64, 128, 256, 512]]\n",
|
|
" BACKBONE:\n",
|
|
" FREEZE_AT: 0\n",
|
|
" NAME: build_resnet_backbone\n",
|
|
" DEVICE: cuda\n",
|
|
" FPN:\n",
|
|
" FUSE_TYPE: sum\n",
|
|
" IN_FEATURES: []\n",
|
|
" NORM: \n",
|
|
" OUT_CHANNELS: 256\n",
|
|
" KEYPOINT_ON: False\n",
|
|
" LOAD_PROPOSALS: False\n",
|
|
" MASK_ON: False\n",
|
|
" META_ARCHITECTURE: OneNet\n",
|
|
" OneNet:\n",
|
|
" ACTIVATION: relu\n",
|
|
" ALPHA: 0.25\n",
|
|
" CLASS_WEIGHT: 2.0\n",
|
|
" DCN: True\n",
|
|
" DECONV_CHANNEL: [2048, 256, 128, 64]\n",
|
|
" DECONV_KERNEL: [4, 4, 4]\n",
|
|
" GAMMA: 2.0\n",
|
|
" GIOU_WEIGHT: 2.0\n",
|
|
" IN_FEATURES: ['res2', 'res3', 'res4', 'res5']\n",
|
|
" L1_WEIGHT: 5.0\n",
|
|
" MODULATE_DEFORM: True\n",
|
|
" NMS: False\n",
|
|
" NUM_CLASSES: 80\n",
|
|
" PRIOR_PROB: 0.01\n",
|
|
" PANOPTIC_FPN:\n",
|
|
" COMBINE:\n",
|
|
" ENABLED: True\n",
|
|
" INSTANCES_CONFIDENCE_THRESH: 0.5\n",
|
|
" OVERLAP_THRESH: 0.5\n",
|
|
" STUFF_AREA_LIMIT: 4096\n",
|
|
" INSTANCE_LOSS_WEIGHT: 1.0\n",
|
|
" PIXEL_MEAN: [123.675, 116.28, 103.53]\n",
|
|
" PIXEL_STD: [58.395, 57.12, 57.375]\n",
|
|
" PROPOSAL_GENERATOR:\n",
|
|
" MIN_SIZE: 0\n",
|
|
" NAME: RPN\n",
|
|
" RESNETS:\n",
|
|
" DEFORM_MODULATED: False\n",
|
|
" DEFORM_NUM_GROUPS: 1\n",
|
|
" DEFORM_ON_PER_STAGE: [False, False, False, False]\n",
|
|
" DEPTH: 50\n",
|
|
" NORM: BN\n",
|
|
" NUM_GROUPS: 1\n",
|
|
" OUT_FEATURES: ['res2', 'res3', 'res4', 'res5']\n",
|
|
" RES2_OUT_CHANNELS: 256\n",
|
|
" RES5_DILATION: 1\n",
|
|
" STEM_OUT_CHANNELS: 64\n",
|
|
" STRIDE_IN_1X1: False\n",
|
|
" WIDTH_PER_GROUP: 64\n",
|
|
" RETINANET:\n",
|
|
" BBOX_REG_LOSS_TYPE: smooth_l1\n",
|
|
" BBOX_REG_WEIGHTS: (1.0, 1.0, 1.0, 1.0)\n",
|
|
" FOCAL_LOSS_ALPHA: 0.25\n",
|
|
" FOCAL_LOSS_GAMMA: 2.0\n",
|
|
" IN_FEATURES: ['p3', 'p4', 'p5', 'p6', 'p7']\n",
|
|
" IOU_LABELS: [0, -1, 1]\n",
|
|
" IOU_THRESHOLDS: [0.4, 0.5]\n",
|
|
" NMS_THRESH_TEST: 0.5\n",
|
|
" NORM: \n",
|
|
" NUM_CLASSES: 80\n",
|
|
" NUM_CONVS: 4\n",
|
|
" PRIOR_PROB: 0.01\n",
|
|
" SCORE_THRESH_TEST: 0.05\n",
|
|
" SMOOTH_L1_LOSS_BETA: 0.1\n",
|
|
" TOPK_CANDIDATES_TEST: 1000\n",
|
|
" ROI_BOX_CASCADE_HEAD:\n",
|
|
" BBOX_REG_WEIGHTS: ((10.0, 10.0, 5.0, 5.0), (20.0, 20.0, 10.0, 10.0), (30.0, 30.0, 15.0, 15.0))\n",
|
|
" IOUS: (0.5, 0.6, 0.7)\n",
|
|
" ROI_BOX_HEAD:\n",
|
|
" BBOX_REG_LOSS_TYPE: smooth_l1\n",
|
|
" BBOX_REG_LOSS_WEIGHT: 1.0\n",
|
|
" BBOX_REG_WEIGHTS: (10.0, 10.0, 5.0, 5.0)\n",
|
|
" CLS_AGNOSTIC_BBOX_REG: False\n",
|
|
" CONV_DIM: 256\n",
|
|
" FC_DIM: 1024\n",
|
|
" NAME: \n",
|
|
" NORM: \n",
|
|
" NUM_CONV: 0\n",
|
|
" NUM_FC: 0\n",
|
|
" POOLER_RESOLUTION: 14\n",
|
|
" POOLER_SAMPLING_RATIO: 0\n",
|
|
" POOLER_TYPE: ROIAlignV2\n",
|
|
" SMOOTH_L1_BETA: 0.0\n",
|
|
" TRAIN_ON_PRED_BOXES: False\n",
|
|
" ROI_HEADS:\n",
|
|
" BATCH_SIZE_PER_IMAGE: 512\n",
|
|
" IN_FEATURES: ['res4']\n",
|
|
" IOU_LABELS: [0, 1]\n",
|
|
" IOU_THRESHOLDS: [0.5]\n",
|
|
" NAME: Res5ROIHeads\n",
|
|
" NMS_THRESH_TEST: 0.5\n",
|
|
" NUM_CLASSES: 80\n",
|
|
" POSITIVE_FRACTION: 0.25\n",
|
|
" PROPOSAL_APPEND_GT: True\n",
|
|
" SCORE_THRESH_TEST: 0.05\n",
|
|
" ROI_KEYPOINT_HEAD:\n",
|
|
" CONV_DIMS: (512, 512, 512, 512, 512, 512, 512, 512)\n",
|
|
" LOSS_WEIGHT: 1.0\n",
|
|
" MIN_KEYPOINTS_PER_IMAGE: 1\n",
|
|
" NAME: KRCNNConvDeconvUpsampleHead\n",
|
|
" NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: True\n",
|
|
" NUM_KEYPOINTS: 17\n",
|
|
" POOLER_RESOLUTION: 14\n",
|
|
" POOLER_SAMPLING_RATIO: 0\n",
|
|
" POOLER_TYPE: ROIAlignV2\n",
|
|
" ROI_MASK_HEAD:\n",
|
|
" CLS_AGNOSTIC_MASK: False\n",
|
|
" CONV_DIM: 256\n",
|
|
" NAME: MaskRCNNConvUpsampleHead\n",
|
|
" NORM: \n",
|
|
" NUM_CONV: 0\n",
|
|
" POOLER_RESOLUTION: 14\n",
|
|
" POOLER_SAMPLING_RATIO: 0\n",
|
|
" POOLER_TYPE: ROIAlignV2\n",
|
|
" RPN:\n",
|
|
" BATCH_SIZE_PER_IMAGE: 256\n",
|
|
" BBOX_REG_LOSS_TYPE: smooth_l1\n",
|
|
" BBOX_REG_LOSS_WEIGHT: 1.0\n",
|
|
" BBOX_REG_WEIGHTS: (1.0, 1.0, 1.0, 1.0)\n",
|
|
" BOUNDARY_THRESH: -1\n",
|
|
" HEAD_NAME: StandardRPNHead\n",
|
|
" IN_FEATURES: ['res4']\n",
|
|
" IOU_LABELS: [0, -1, 1]\n",
|
|
" IOU_THRESHOLDS: [0.3, 0.7]\n",
|
|
" LOSS_WEIGHT: 1.0\n",
|
|
" NMS_THRESH: 0.7\n",
|
|
" POSITIVE_FRACTION: 0.5\n",
|
|
" POST_NMS_TOPK_TEST: 1000\n",
|
|
" POST_NMS_TOPK_TRAIN: 2000\n",
|
|
" PRE_NMS_TOPK_TEST: 6000\n",
|
|
" PRE_NMS_TOPK_TRAIN: 12000\n",
|
|
" SMOOTH_L1_BETA: 0.0\n",
|
|
" SEM_SEG_HEAD:\n",
|
|
" COMMON_STRIDE: 4\n",
|
|
" CONVS_DIM: 128\n",
|
|
" IGNORE_VALUE: 255\n",
|
|
" IN_FEATURES: ['p2', 'p3', 'p4', 'p5']\n",
|
|
" LOSS_WEIGHT: 1.0\n",
|
|
" NAME: SemSegFPNHead\n",
|
|
" NORM: GN\n",
|
|
" NUM_CLASSES: 54\n",
|
|
" WEIGHTS: detectron2://ImageNetPretrained/torchvision/R-50.pkl\n",
|
|
"OUTPUT_DIR: output_onenet_r50dcn\n",
|
|
"SEED: 40244023\n",
|
|
"SOLVER:\n",
|
|
" AMP:\n",
|
|
" ENABLED: False\n",
|
|
" BACKBONE_MULTIPLIER: 1.0\n",
|
|
" BASE_LR: 5e-05\n",
|
|
" BIAS_LR_FACTOR: 1.0\n",
|
|
" CHECKPOINT_PERIOD: 5000\n",
|
|
" CLIP_GRADIENTS:\n",
|
|
" CLIP_TYPE: full_model\n",
|
|
" CLIP_VALUE: 1.0\n",
|
|
" ENABLED: False\n",
|
|
" NORM_TYPE: 2.0\n",
|
|
" GAMMA: 0.1\n",
|
|
" IMS_PER_BATCH: 64\n",
|
|
" LR_SCHEDULER_NAME: WarmupMultiStepLR\n",
|
|
" MAX_ITER: 270000\n",
|
|
" MOMENTUM: 0.9\n",
|
|
" NESTEROV: False\n",
|
|
" OPTIMIZER: ADAMW\n",
|
|
" REFERENCE_WORLD_SIZE: 0\n",
|
|
" STEPS: (210000, 250000)\n",
|
|
" WARMUP_FACTOR: 0.01\n",
|
|
" WARMUP_ITERS: 1000\n",
|
|
" WARMUP_METHOD: linear\n",
|
|
" WEIGHT_DECAY: 0.0001\n",
|
|
" WEIGHT_DECAY_BIAS: 0.0001\n",
|
|
" WEIGHT_DECAY_NORM: 0.0\n",
|
|
"TEST:\n",
|
|
" AUG:\n",
|
|
" ENABLED: False\n",
|
|
" FLIP: True\n",
|
|
" MAX_SIZE: 4000\n",
|
|
" MIN_SIZES: (400, 500, 600, 700, 800, 900, 1000, 1100, 1200)\n",
|
|
" DETECTIONS_PER_IMAGE: 100\n",
|
|
" EVAL_PERIOD: 7330\n",
|
|
" EXPECTED_RESULTS: []\n",
|
|
" KEYPOINT_OKS_SIGMAS: []\n",
|
|
" PRECISE_BN:\n",
|
|
" ENABLED: False\n",
|
|
" NUM_ITER: 200\n",
|
|
"VERSION: 2\n",
|
|
"VIS_PERIOD: 0\n",
|
|
"\u001b[32m[12/17 11:48:48 detectron2]: \u001b[0mFull config saved to output_onenet_r50dcn/config.yaml\n",
|
|
"\u001b[32m[12/17 11:48:52 d2.engine.defaults]: \u001b[0mModel:\n",
|
|
"OneNet(\n",
|
|
" (backbone): ResNet(\n",
|
|
" (stem): BasicStem(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False\n",
|
|
" (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (res2): Sequential(\n",
|
|
" (0): BottleneckBlock(\n",
|
|
" (shortcut): Conv2d(\n",
|
|
" 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (1): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (2): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (res3): Sequential(\n",
|
|
" (0): BottleneckBlock(\n",
|
|
" (shortcut): Conv2d(\n",
|
|
" 256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (1): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (2): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (3): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (res4): Sequential(\n",
|
|
" (0): BottleneckBlock(\n",
|
|
" (shortcut): Conv2d(\n",
|
|
" 512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
|
|
" (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (1): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (2): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (3): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (4): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (5): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (res5): Sequential(\n",
|
|
" (0): BottleneckBlock(\n",
|
|
" (shortcut): Conv2d(\n",
|
|
" 1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False\n",
|
|
" (norm): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (1): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (2): BottleneckBlock(\n",
|
|
" (conv1): Conv2d(\n",
|
|
" 2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv2): Conv2d(\n",
|
|
" 512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" (conv3): Conv2d(\n",
|
|
" 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False\n",
|
|
" (norm): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" )\n",
|
|
" )\n",
|
|
" )\n",
|
|
" )\n",
|
|
" (head): Head(\n",
|
|
" (deconv): CenternetDeconv(\n",
|
|
" (deconv1): DCNDeconvLayer(\n",
|
|
" (dcn_offset): Conv2d(2048, 27, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
|
|
" (dcn): ModulatedDeformConv(in_channels=2048, out_channels=256, kernel_size=(3, 3), stride=1, padding=1, dilation=1, groups=1, deformable_groups=1, bias=False)\n",
|
|
" (dcn_bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" (up_sample): ConvTranspose2d(256, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)\n",
|
|
" (up_bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" (relu): ReLU()\n",
|
|
" )\n",
|
|
" (lateral_conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1))\n",
|
|
" (deconv2): DCNDeconvLayer(\n",
|
|
" (dcn_offset): Conv2d(256, 27, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
|
|
" (dcn): ModulatedDeformConv(in_channels=256, out_channels=128, kernel_size=(3, 3), stride=1, padding=1, dilation=1, groups=1, deformable_groups=1, bias=False)\n",
|
|
" (dcn_bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" (up_sample): ConvTranspose2d(128, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)\n",
|
|
" (up_bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" (relu): ReLU()\n",
|
|
" )\n",
|
|
" (lateral_conv2): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1))\n",
|
|
" (deconv3): DCNDeconvLayer(\n",
|
|
" (dcn_offset): Conv2d(128, 27, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
|
|
" (dcn): ModulatedDeformConv(in_channels=128, out_channels=64, kernel_size=(3, 3), stride=1, padding=1, dilation=1, groups=1, deformable_groups=1, bias=False)\n",
|
|
" (dcn_bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" (up_sample): ConvTranspose2d(64, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)\n",
|
|
" (up_bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
|
|
" (relu): ReLU()\n",
|
|
" )\n",
|
|
" (lateral_conv3): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))\n",
|
|
" (output_conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
|
|
" )\n",
|
|
" (feat1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
|
|
" (cls_score): Conv2d(64, 80, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
|
|
" (ltrb_pred): Conv2d(64, 4, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
|
|
" )\n",
|
|
" (criterion): SetCriterion(\n",
|
|
" (matcher): MinCostMatcher()\n",
|
|
" )\n",
|
|
")\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"projects/OneNet/train_net.py\", line 140, in <module>\n",
|
|
" args=(args,),\n",
|
|
" File \"/content/OneNet/detectron2/engine/launch.py\", line 62, in launch\n",
|
|
" main_func(*args)\n",
|
|
" File \"projects/OneNet/train_net.py\", line 126, in main\n",
|
|
" trainer = Trainer(cfg)\n",
|
|
" File \"/content/OneNet/detectron2/engine/defaults.py\", line 284, in __init__\n",
|
|
" data_loader = self.build_train_loader(cfg)\n",
|
|
" File \"projects/OneNet/train_net.py\", line 50, in build_train_loader\n",
|
|
" return build_detection_train_loader(cfg, mapper=mapper)\n",
|
|
" File \"/content/OneNet/detectron2/config/config.py\", line 201, in wrapped\n",
|
|
" explicit_args = _get_args_from_config(from_config, *args, **kwargs)\n",
|
|
" File \"/content/OneNet/detectron2/config/config.py\", line 236, in _get_args_from_config\n",
|
|
" ret = from_config_func(*args, **kwargs)\n",
|
|
" File \"/content/OneNet/detectron2/data/build.py\", line 309, in _train_loader_from_config\n",
|
|
" proposal_files=cfg.DATASETS.PROPOSAL_FILES_TRAIN if cfg.MODEL.LOAD_PROPOSALS else None,\n",
|
|
" File \"/content/OneNet/detectron2/data/build.py\", line 222, in get_detection_dataset_dicts\n",
|
|
" dataset_dicts = [DatasetCatalog.get(dataset_name) for dataset_name in dataset_names]\n",
|
|
" File \"/content/OneNet/detectron2/data/build.py\", line 222, in <listcomp>\n",
|
|
" dataset_dicts = [DatasetCatalog.get(dataset_name) for dataset_name in dataset_names]\n",
|
|
" File \"/content/OneNet/detectron2/data/catalog.py\", line 58, in get\n",
|
|
" return f()\n",
|
|
" File \"/content/OneNet/detectron2/data/datasets/coco.py\", line 469, in <lambda>\n",
|
|
" DatasetCatalog.register(name, lambda: load_coco_json(json_file, image_root, name))\n",
|
|
" File \"/content/OneNet/detectron2/data/datasets/coco.py\", line 60, in load_coco_json\n",
|
|
" coco_api = COCO(json_file)\n",
|
|
" File \"/usr/local/lib/python3.6/dist-packages/pycocotools/coco.py\", line 84, in __init__\n",
|
|
" with open(annotation_file, 'r') as f:\n",
|
|
"FileNotFoundError: [Errno 2] No such file or directory: 'datasets/coco/annotations/instances_train2017.json'\n"
|
|
],
|
|
"name": "stdout"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "FEQFguZWrMRm"
|
|
},
|
|
"source": [
|
|
"# Evaluate"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "-cm7zqKrYJlj",
|
|
"outputId": "58e32b67-32cd-4e89-a8c7-24ce262c9e04"
|
|
},
|
|
"source": [
|
|
"!python projects/OneNet/train_net.py --num-gpus 1 \\\r\n",
|
|
" --config-file projects/OneNet/configs/onenet.res50.dcn.yaml \\\r\n",
|
|
" --eval-only MODEL.WEIGHTS path/to/model.pth"
|
|
],
|
|
"execution_count": null,
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"text": [
|
|
"** fvcore version of PathManager will be deprecated soon. **\n",
|
|
"** Please migrate to the version in iopath repo. **\n",
|
|
"https://github.com/facebookresearch/iopath \n",
|
|
"\n",
|
|
"** fvcore version of PathManager will be deprecated soon. **\n",
|
|
"** Please migrate to the version in iopath repo. **\n",
|
|
"https://github.com/facebookresearch/iopath \n",
|
|
"\n",
|
|
"Command Line Args: Namespace(config_file='projects/OneNet/configs/onenet.res50.dcn.yaml', dist_url='tcp://127.0.0.1:49152', eval_only=True, machine_rank=0, num_gpus=1, num_machines=1, opts=['MODEL.WEIGHTS', 'path/to/model.pth'], resume=False)\n",
|
|
"\u001b[32m[12/17 08:30:33 detectron2]: \u001b[0mRank of current process: 0. World size: 1\n",
|
|
"/usr/local/lib/python3.6/dist-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: The NVIDIA driver on your system is too old (found version 10010). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at /pytorch/c10/cuda/CUDAFunctions.cpp:100.)\n",
|
|
" return torch._C._cuda_getDeviceCount() > 0\n",
|
|
"No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'\n",
|
|
"\u001b[32m[12/17 08:30:34 detectron2]: \u001b[0mEnvironment info:\n",
|
|
"--------------------- ---------------------------------------------------------\n",
|
|
"sys.platform linux\n",
|
|
"Python 3.6.9 (default, Oct 8 2020, 12:12:24) [GCC 8.4.0]\n",
|
|
"numpy 1.18.5\n",
|
|
"detectron2 0.3 @/content/OneNet/detectron2\n",
|
|
"Compiler GCC 7.5\n",
|
|
"CUDA compiler CUDA 10.1\n",
|
|
"DETECTRON2_ENV_MODULE <not set>\n",
|
|
"PyTorch 1.7.1 @/usr/local/lib/python3.6/dist-packages/torch\n",
|
|
"PyTorch debug build False\n",
|
|
"GPU available False\n",
|
|
"Pillow 7.0.0\n",
|
|
"torchvision 0.8.2 @/usr/local/lib/python3.6/dist-packages/torchvision\n",
|
|
"fvcore 0.1.2.post20201216\n",
|
|
"cv2 4.1.2\n",
|
|
"--------------------- ---------------------------------------------------------\n",
|
|
"PyTorch built with:\n",
|
|
" - GCC 7.3\n",
|
|
" - C++ Version: 201402\n",
|
|
" - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications\n",
|
|
" - Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)\n",
|
|
" - OpenMP 201511 (a.k.a. OpenMP 4.5)\n",
|
|
" - NNPACK is enabled\n",
|
|
" - CPU capability usage: AVX2\n",
|
|
" - Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, \n",
|
|
"\n",
|
|
"\u001b[32m[12/17 08:30:34 detectron2]: \u001b[0mCommand line arguments: Namespace(config_file='projects/OneNet/configs/onenet.res50.dcn.yaml', dist_url='tcp://127.0.0.1:49152', eval_only=True, machine_rank=0, num_gpus=1, num_machines=1, opts=['MODEL.WEIGHTS', 'path/to/model.pth'], resume=False)\n",
|
|
"\u001b[32m[12/17 08:30:34 detectron2]: \u001b[0mContents of args.config_file=projects/OneNet/configs/onenet.res50.dcn.yaml:\n",
|
|
"_BASE_: \"Base-OneNet.yaml\"\n",
|
|
"MODEL:\n",
|
|
" WEIGHTS: \"detectron2://ImageNetPretrained/torchvision/R-50.pkl\"\n",
|
|
" BACKBONE:\n",
|
|
" FREEZE_AT: 0\n",
|
|
" RESNETS:\n",
|
|
" NORM: \"BN\"\n",
|
|
" DEPTH: 50\n",
|
|
" STRIDE_IN_1X1: False\n",
|
|
" OneNet:\n",
|
|
" DCN: True\n",
|
|
" NUM_CLASSES: 80\n",
|
|
"DATASETS:\n",
|
|
" TRAIN: (\"coco_2017_train\",)\n",
|
|
" TEST: (\"coco_2017_val\",)\n",
|
|
"SOLVER:\n",
|
|
" IMS_PER_BATCH: 64\n",
|
|
" STEPS: (210000, 250000)\n",
|
|
" MAX_ITER: 270000\n",
|
|
"INPUT:\n",
|
|
" CROP:\n",
|
|
" ENABLED: True\n",
|
|
" FORMAT: \"RGB\"\n",
|
|
"OUTPUT_DIR: 'output_onenet_r50dcn'\n",
|
|
"\n",
|
|
"\u001b[32m[12/17 08:30:34 detectron2]: \u001b[0mRunning with full config:\n",
|
|
"CUDNN_BENCHMARK: False\n",
|
|
"DATALOADER:\n",
|
|
" ASPECT_RATIO_GROUPING: True\n",
|
|
" FILTER_EMPTY_ANNOTATIONS: False\n",
|
|
" NUM_WORKERS: 4\n",
|
|
" REPEAT_THRESHOLD: 0.0\n",
|
|
" SAMPLER_TRAIN: TrainingSampler\n",
|
|
"DATASETS:\n",
|
|
" PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000\n",
|
|
" PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000\n",
|
|
" PROPOSAL_FILES_TEST: ()\n",
|
|
" PROPOSAL_FILES_TRAIN: ()\n",
|
|
" TEST: ('coco_2017_val',)\n",
|
|
" TRAIN: ('coco_2017_train',)\n",
|
|
"GLOBAL:\n",
|
|
" HACK: 1.0\n",
|
|
"INPUT:\n",
|
|
" CROP:\n",
|
|
" ENABLED: True\n",
|
|
" SIZE: [384, 600]\n",
|
|
" TYPE: absolute_range\n",
|
|
" FORMAT: RGB\n",
|
|
" MASK_FORMAT: polygon\n",
|
|
" MAX_SIZE_TEST: 853\n",
|
|
" MAX_SIZE_TRAIN: 853\n",
|
|
" MIN_SIZE_TEST: 512\n",
|
|
" MIN_SIZE_TRAIN: (416, 448, 480, 512)\n",
|
|
" MIN_SIZE_TRAIN_SAMPLING: choice\n",
|
|
" RANDOM_FLIP: horizontal\n",
|
|
"MODEL:\n",
|
|
" ANCHOR_GENERATOR:\n",
|
|
" ANGLES: [[-90, 0, 90]]\n",
|
|
" ASPECT_RATIOS: [[0.5, 1.0, 2.0]]\n",
|
|
" NAME: DefaultAnchorGenerator\n",
|
|
" OFFSET: 0.0\n",
|
|
" SIZES: [[32, 64, 128, 256, 512]]\n",
|
|
" BACKBONE:\n",
|
|
" FREEZE_AT: 0\n",
|
|
" NAME: build_resnet_backbone\n",
|
|
" DEVICE: cuda\n",
|
|
" FPN:\n",
|
|
" FUSE_TYPE: sum\n",
|
|
" IN_FEATURES: []\n",
|
|
" NORM: \n",
|
|
" OUT_CHANNELS: 256\n",
|
|
" KEYPOINT_ON: False\n",
|
|
" LOAD_PROPOSALS: False\n",
|
|
" MASK_ON: False\n",
|
|
" META_ARCHITECTURE: OneNet\n",
|
|
" OneNet:\n",
|
|
" ACTIVATION: relu\n",
|
|
" ALPHA: 0.25\n",
|
|
" CLASS_WEIGHT: 2.0\n",
|
|
" DCN: True\n",
|
|
" DECONV_CHANNEL: [2048, 256, 128, 64]\n",
|
|
" DECONV_KERNEL: [4, 4, 4]\n",
|
|
" GAMMA: 2.0\n",
|
|
" GIOU_WEIGHT: 2.0\n",
|
|
" IN_FEATURES: ['res2', 'res3', 'res4', 'res5']\n",
|
|
" L1_WEIGHT: 5.0\n",
|
|
" MODULATE_DEFORM: True\n",
|
|
" NMS: False\n",
|
|
" NUM_CLASSES: 80\n",
|
|
" PRIOR_PROB: 0.01\n",
|
|
" PANOPTIC_FPN:\n",
|
|
" COMBINE:\n",
|
|
" ENABLED: True\n",
|
|
" INSTANCES_CONFIDENCE_THRESH: 0.5\n",
|
|
" OVERLAP_THRESH: 0.5\n",
|
|
" STUFF_AREA_LIMIT: 4096\n",
|
|
" INSTANCE_LOSS_WEIGHT: 1.0\n",
|
|
" PIXEL_MEAN: [123.675, 116.28, 103.53]\n",
|
|
" PIXEL_STD: [58.395, 57.12, 57.375]\n",
|
|
" PROPOSAL_GENERATOR:\n",
|
|
" MIN_SIZE: 0\n",
|
|
" NAME: RPN\n",
|
|
" RESNETS:\n",
|
|
" DEFORM_MODULATED: False\n",
|
|
" DEFORM_NUM_GROUPS: 1\n",
|
|
" DEFORM_ON_PER_STAGE: [False, False, False, False]\n",
|
|
" DEPTH: 50\n",
|
|
" NORM: BN\n",
|
|
" NUM_GROUPS: 1\n",
|
|
" OUT_FEATURES: ['res2', 'res3', 'res4', 'res5']\n",
|
|
" RES2_OUT_CHANNELS: 256\n",
|
|
" RES5_DILATION: 1\n",
|
|
" STEM_OUT_CHANNELS: 64\n",
|
|
" STRIDE_IN_1X1: False\n",
|
|
" WIDTH_PER_GROUP: 64\n",
|
|
" RETINANET:\n",
|
|
" BBOX_REG_LOSS_TYPE: smooth_l1\n",
|
|
" BBOX_REG_WEIGHTS: (1.0, 1.0, 1.0, 1.0)\n",
|
|
" FOCAL_LOSS_ALPHA: 0.25\n",
|
|
" FOCAL_LOSS_GAMMA: 2.0\n",
|
|
" IN_FEATURES: ['p3', 'p4', 'p5', 'p6', 'p7']\n",
|
|
" IOU_LABELS: [0, -1, 1]\n",
|
|
" IOU_THRESHOLDS: [0.4, 0.5]\n",
|
|
" NMS_THRESH_TEST: 0.5\n",
|
|
" NORM: \n",
|
|
" NUM_CLASSES: 80\n",
|
|
" NUM_CONVS: 4\n",
|
|
" PRIOR_PROB: 0.01\n",
|
|
" SCORE_THRESH_TEST: 0.05\n",
|
|
" SMOOTH_L1_LOSS_BETA: 0.1\n",
|
|
" TOPK_CANDIDATES_TEST: 1000\n",
|
|
" ROI_BOX_CASCADE_HEAD:\n",
|
|
" BBOX_REG_WEIGHTS: ((10.0, 10.0, 5.0, 5.0), (20.0, 20.0, 10.0, 10.0), (30.0, 30.0, 15.0, 15.0))\n",
|
|
" IOUS: (0.5, 0.6, 0.7)\n",
|
|
" ROI_BOX_HEAD:\n",
|
|
" BBOX_REG_LOSS_TYPE: smooth_l1\n",
|
|
" BBOX_REG_LOSS_WEIGHT: 1.0\n",
|
|
" BBOX_REG_WEIGHTS: (10.0, 10.0, 5.0, 5.0)\n",
|
|
" CLS_AGNOSTIC_BBOX_REG: False\n",
|
|
" CONV_DIM: 256\n",
|
|
" FC_DIM: 1024\n",
|
|
" NAME: \n",
|
|
" NORM: \n",
|
|
" NUM_CONV: 0\n",
|
|
" NUM_FC: 0\n",
|
|
" POOLER_RESOLUTION: 14\n",
|
|
" POOLER_SAMPLING_RATIO: 0\n",
|
|
" POOLER_TYPE: ROIAlignV2\n",
|
|
" SMOOTH_L1_BETA: 0.0\n",
|
|
" TRAIN_ON_PRED_BOXES: False\n",
|
|
" ROI_HEADS:\n",
|
|
" BATCH_SIZE_PER_IMAGE: 512\n",
|
|
" IN_FEATURES: ['res4']\n",
|
|
" IOU_LABELS: [0, 1]\n",
|
|
" IOU_THRESHOLDS: [0.5]\n",
|
|
" NAME: Res5ROIHeads\n",
|
|
" NMS_THRESH_TEST: 0.5\n",
|
|
" NUM_CLASSES: 80\n",
|
|
" POSITIVE_FRACTION: 0.25\n",
|
|
" PROPOSAL_APPEND_GT: True\n",
|
|
" SCORE_THRESH_TEST: 0.05\n",
|
|
" ROI_KEYPOINT_HEAD:\n",
|
|
" CONV_DIMS: (512, 512, 512, 512, 512, 512, 512, 512)\n",
|
|
" LOSS_WEIGHT: 1.0\n",
|
|
" MIN_KEYPOINTS_PER_IMAGE: 1\n",
|
|
" NAME: KRCNNConvDeconvUpsampleHead\n",
|
|
" NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: True\n",
|
|
" NUM_KEYPOINTS: 17\n",
|
|
" POOLER_RESOLUTION: 14\n",
|
|
" POOLER_SAMPLING_RATIO: 0\n",
|
|
" POOLER_TYPE: ROIAlignV2\n",
|
|
" ROI_MASK_HEAD:\n",
|
|
" CLS_AGNOSTIC_MASK: False\n",
|
|
" CONV_DIM: 256\n",
|
|
" NAME: MaskRCNNConvUpsampleHead\n",
|
|
" NORM: \n",
|
|
" NUM_CONV: 0\n",
|
|
" POOLER_RESOLUTION: 14\n",
|
|
" POOLER_SAMPLING_RATIO: 0\n",
|
|
" POOLER_TYPE: ROIAlignV2\n",
|
|
" RPN:\n",
|
|
" BATCH_SIZE_PER_IMAGE: 256\n",
|
|
" BBOX_REG_LOSS_TYPE: smooth_l1\n",
|
|
" BBOX_REG_LOSS_WEIGHT: 1.0\n",
|
|
" BBOX_REG_WEIGHTS: (1.0, 1.0, 1.0, 1.0)\n",
|
|
" BOUNDARY_THRESH: -1\n",
|
|
" HEAD_NAME: StandardRPNHead\n",
|
|
" IN_FEATURES: ['res4']\n",
|
|
" IOU_LABELS: [0, -1, 1]\n",
|
|
" IOU_THRESHOLDS: [0.3, 0.7]\n",
|
|
" LOSS_WEIGHT: 1.0\n",
|
|
" NMS_THRESH: 0.7\n",
|
|
" POSITIVE_FRACTION: 0.5\n",
|
|
" POST_NMS_TOPK_TEST: 1000\n",
|
|
" POST_NMS_TOPK_TRAIN: 2000\n",
|
|
" PRE_NMS_TOPK_TEST: 6000\n",
|
|
" PRE_NMS_TOPK_TRAIN: 12000\n",
|
|
" SMOOTH_L1_BETA: 0.0\n",
|
|
" SEM_SEG_HEAD:\n",
|
|
" COMMON_STRIDE: 4\n",
|
|
" CONVS_DIM: 128\n",
|
|
" IGNORE_VALUE: 255\n",
|
|
" IN_FEATURES: ['p2', 'p3', 'p4', 'p5']\n",
|
|
" LOSS_WEIGHT: 1.0\n",
|
|
" NAME: SemSegFPNHead\n",
|
|
" NORM: GN\n",
|
|
" NUM_CLASSES: 54\n",
|
|
" WEIGHTS: path/to/model.pth\n",
|
|
"OUTPUT_DIR: output_onenet_r50dcn\n",
|
|
"SEED: 40244023\n",
|
|
"SOLVER:\n",
|
|
" AMP:\n",
|
|
" ENABLED: False\n",
|
|
" BACKBONE_MULTIPLIER: 1.0\n",
|
|
" BASE_LR: 5e-05\n",
|
|
" BIAS_LR_FACTOR: 1.0\n",
|
|
" CHECKPOINT_PERIOD: 5000\n",
|
|
" CLIP_GRADIENTS:\n",
|
|
" CLIP_TYPE: full_model\n",
|
|
" CLIP_VALUE: 1.0\n",
|
|
" ENABLED: False\n",
|
|
" NORM_TYPE: 2.0\n",
|
|
" GAMMA: 0.1\n",
|
|
" IMS_PER_BATCH: 64\n",
|
|
" LR_SCHEDULER_NAME: WarmupMultiStepLR\n",
|
|
" MAX_ITER: 270000\n",
|
|
" MOMENTUM: 0.9\n",
|
|
" NESTEROV: False\n",
|
|
" OPTIMIZER: ADAMW\n",
|
|
" REFERENCE_WORLD_SIZE: 0\n",
|
|
" STEPS: (210000, 250000)\n",
|
|
" WARMUP_FACTOR: 0.01\n",
|
|
" WARMUP_ITERS: 1000\n",
|
|
" WARMUP_METHOD: linear\n",
|
|
" WEIGHT_DECAY: 0.0001\n",
|
|
" WEIGHT_DECAY_BIAS: 0.0001\n",
|
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" WEIGHT_DECAY_NORM: 0.0\n",
|
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"TEST:\n",
|
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" AUG:\n",
|
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" ENABLED: False\n",
|
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" FLIP: True\n",
|
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" MAX_SIZE: 4000\n",
|
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" MIN_SIZES: (400, 500, 600, 700, 800, 900, 1000, 1100, 1200)\n",
|
|
" DETECTIONS_PER_IMAGE: 100\n",
|
|
" EVAL_PERIOD: 7330\n",
|
|
" EXPECTED_RESULTS: []\n",
|
|
" KEYPOINT_OKS_SIGMAS: []\n",
|
|
" PRECISE_BN:\n",
|
|
" ENABLED: False\n",
|
|
" NUM_ITER: 200\n",
|
|
"VERSION: 2\n",
|
|
"VIS_PERIOD: 0\n",
|
|
"\u001b[32m[12/17 08:30:34 detectron2]: \u001b[0mFull config saved to output_onenet_r50dcn/config.yaml\n",
|
|
"Traceback (most recent call last):\n",
|
|
" File \"projects/OneNet/train_net.py\", line 140, in <module>\n",
|
|
" args=(args,),\n",
|
|
" File \"/content/OneNet/detectron2/engine/launch.py\", line 62, in launch\n",
|
|
" main_func(*args)\n",
|
|
" File \"projects/OneNet/train_net.py\", line 119, in main\n",
|
|
" model = Trainer.build_model(cfg)\n",
|
|
" File \"/content/OneNet/detectron2/engine/defaults.py\", line 441, in build_model\n",
|
|
" model = build_model(cfg)\n",
|
|
" File \"/content/OneNet/detectron2/modeling/meta_arch/build.py\", line 21, in build_model\n",
|
|
" model = META_ARCH_REGISTRY.get(meta_arch)(cfg)\n",
|
|
" File \"/content/OneNet/projects/OneNet/onenet/detector.py\", line 77, in __init__\n",
|
|
" pixel_mean = torch.Tensor(cfg.MODEL.PIXEL_MEAN).to(self.device).view(3, 1, 1)\n",
|
|
" File \"/usr/local/lib/python3.6/dist-packages/torch/cuda/__init__.py\", line 172, in _lazy_init\n",
|
|
" torch._C._cuda_init()\n",
|
|
"RuntimeError: The NVIDIA driver on your system is too old (found version 10010). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver.\n"
|
|
],
|
|
"name": "stdout"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "bxiRGTX3rR2-"
|
|
},
|
|
"source": [
|
|
"# Visualize\r\n",
|
|
"install opencv additinoally for visualize"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"metadata": {
|
|
"id": "qRpGotxpzzZ-"
|
|
},
|
|
"source": [
|
|
"!python demo/demo.py\\\r\n",
|
|
" --config-file projects/OneNet/configs/onenet.res50.dcn.yaml \\\r\n",
|
|
" --input path/to/images --output path/to/save_images --confidence-threshold 0.4 \\\r\n",
|
|
" --opts MODEL.WEIGHTS path/to/model.pth"
|
|
],
|
|
"execution_count": null,
|
|
"outputs": []
|
|
}
|
|
]
|
|
} |