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    MMCV

    安装

    pip install mmcv-full==1.3.0 -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html

    MMPose

    安装

    先安装MMCV， 然后再进行下面的安装

    # install mmpose
git clone git@github.com:open-mmlab/mmpose.git
cd mmpose
pip install -r requirements.txt
python setup.py develop

    要求numpy版本 1.20.0

    run demo

    Using gt human bounding boxes as input

    python demo/top_down_img_demo.py \
    configs/top_down/hrnet/coco/hrnet_w48_coco_256x192.py \
    https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w48_coco_256x192-b9e0b3ab_20200708.pth \
    --img-root tests/data/coco/ --json-file tests/data/coco/test_coco.json \
    --out-img-root vis_results

    Using mmdet for human bounding box detection

    python demo/top_down_img_demo_with_mmdet.py \
    demo/mmdetection_cfg/faster_rcnn_r50_fpn_1x_coco.py \
    http://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth \
    configs/top_down/hrnet/coco/hrnet_w48_coco_256x192.py \
    https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w48_coco_256x192-b9e0b3ab_20200708.pth \
    --img-root tests/data/coco/ \
    --img 000000196141.jpg \
    --out-img-root vis_results

    2D Human Pose Top-Down Video Demo

    python demo/top_down_video_demo_with_mmdet.py \
    demo/mmdetection_cfg/faster_rcnn_r50_fpn_1x_coco.py \
    http://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth \
    configs/top_down/hrnet/coco/hrnet_w48_coco_256x192.py \
    https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w48_coco_256x192-b9e0b3ab_20200708.pth \
    --video-path demo/demo_video.mp4 \
    --out-video-root vis_results

    2D Human Pose Bottom-Up Image Demo

    python demo/bottom_up_img_demo.py \
    configs/bottom_up/hrnet/coco/hrnet_w32_coco_512x512.py \
    https://download.openmmlab.com/mmpose/bottom_up/hrnet_w32_coco_512x512-bcb8c247_20200816.pth \
    --img-root tests/data/coco/ --json-file tests/data/coco/test_coco.json \
    --out-img-root vis_results

    2D Human Pose Bottom-Up Video Demo

    python demo/bottom_up_video_demo.py \
    configs/bottom_up/hrnet/coco/hrnet_w32_coco_512x512.py \
    https://download.openmmlab.com/mmpose/bottom_up/hrnet_w32_coco_512x512-bcb8c247_20200816.pth \
    --video-path demo/demo_video.mp4 \
    --out-video-root vis_results

    Speed Up Inference

    对于自顶向下的模型，尝试编辑配置文件。例如：

    对于自底向上的模型，尝试编辑配置文件。例如：

    MMDetection

    安装

    版本对应关系：

    MMDetection version MMCV version
    master mmcv-full>=1.2.4, <1.4.0
    2.11.0 mmcv-full>=1.2.4, <1.4.0
    2.10.0 mmcv-full>=1.2.4, <1.4.0
    2.9.0 mmcv-full>=1.2.4, <1.4.0
    2.8.0 mmcv-full>=1.2.4, <1.4.0
    2.7.0 mmcv-full>=1.1.5, <1.4.0
    2.6.0 mmcv-full>=1.1.5, <1.4.0
    2.5.0 mmcv-full>=1.1.5, <1.4.0
    2.4.0 mmcv-full>=1.1.1, <1.4.0
    2.3.0 mmcv-full == 1.0.5
    2.3.0rc0 mmcv-full>=1.0.2
    2.2.1 mmcv == 0.6.2
    2.2.0 mmcv == 0.6.2
    2.1.0 mmcv>=0.5.9, <=0.6.1
    2.0.0 mmcv>=0.5.1, <=0.5.8

    先安装MMCV， 然后再进行下面的安装

    # install mmdetection
git clone https://github.com/open-mmlab/mmdetection.git
cd mmdetection
pip install -r requirements/build.txt
pip install -v -e .

    MMTracking

    安装

    先安装MMCV和MMDetection，然后执行：

    git clone https://github.com/open-mmlab/mmtracking.git
cd mmtracking

    安装：

    pip install -r requirements/build.txt
pip install -v -e .  # or "python setup.py develop"