simpledet 的配置

• simpledet 的配置

• 1. 經過 docker 配置 simpledet

• 1.1 系統要求

  ubuntu16.04

  python >=3.5

• 1.2 下載 docker 鏡像

  匹配的版本爲 ubuntu16.04， cuda9.0， cudnn7， python3。

  https://gitlab.com/nvidia/cuda/blob/ubuntu16.04/9.0/devel/cudnn7/Dockerfile

• 1.3 運行 docker

  nvidia-docker run -v $HOST-SIMPLEDET-DIR:$CONTAINER-WORKDIR -it nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04 bash

• 1.4 安裝所需環境

# Install dependency
sudo apt-get update
sudo apt-get install -y build-essential git
sudo apt-get install -y libopenblas-dev

• 1.5 下載 simpledet 和 pycocotools, mxnext 項目

git clone <https://github.com/TuSimple/simpledet.git>
cd /path/to/simpledet
make

# Install a patched cocotools for python3
git clone <https://github.com/RogerChern/cocoapi>
cd cocoapi/PythonAPI
python3 setup.py install

# setup mxnext, a wrapper of mxnet symbolic API
cd /path/to/simpledet
git clone <https://github.com/RogerChern/mxnext>

• 1.6 安裝mxnet

# Specify simpledet directory
export SIMPLEDET_DIR=/path/to/simpledet
export COCOAPI_DIR=/path/to/cocoapi

git clone https://github.com/apache/incubator-mxnet mxnet
cd mxnet
git checkout 1.3.1
git submodule init
git submodule update
echo "USE_OPENCV = 0" >> ./config.mk
echo "USE_BLAS = openblas" >> ./config.mk
echo "USE_CUDA = 1" >> ./config.mk
echo "USE_CUDA_PATH = /usr/local/cuda" >> ./config.mk
echo "USE_CUDNN = 1" >> ./config.mk
echo "USE_NCCL = 1" >> ./config.mk
echo "USE_DIST_KVSTORE = 1" >> ./config.mk
cp -r $SIMPLEDET_DIR/operator_cxx/* src/operator/
mkdir -p src/coco_api
cp -r $COCOAPI_DIR/common src/coco_api/
make -j
cd python
python3 setup.py install

• 2. 使用 coco 測試集進行模型測試

• 2.1 下載模型

  在 simpledet 目錄下新建 experiments 目錄，並將下載好的模型（https://github.com/TuSimple/simpledet/tree/master/models/tridentnet）放至該路徑下，如

  experiments/
    tridentnet_r101v2c4_c5_1x/
        checkpoint-0006.params
        checkpoint-symbol.json
        log.txt
        coco_minival2014_result.json

• 2.2 構建 coco roidb 測試集，將coco數據集按如下目錄結構進行存放

data/
    coco/
        annotations/
            instances_train2014.json
            instances_valminusminival2014.json
            instances_minival2014.json
            image_info_testdev2017.json
        images/
            train2014
            val2014
            test2017

• 2.3 執行轉換命令，例如：

python3 utils/generate_roidb.py --dataset coco --dataset-split train2014
python3 utils/generate_roidb.py --dataset coco --dataset-split valminusminival2014
python3 utils/generate_roidb.py --dataset coco --dataset-split minival2014
python3 utils/generate_roidb.py --dataset coco --dataset-split test-dev2017

• 2.4 測試

python3 detection_test.py --config config/detection_config.py

• 3. 單張圖像的檢測

詳見 https://github.com/danpe1327/simpledet/blob/master/detect_image.py