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openmmlab_work's Introduction

openmmlab_work

这是openmmlab的实战作业,感谢子豪兄提供的代码!!

我利用anaconda创建了3.8.16的python虚拟环境:openmmlab 作为本次课程的专用环境

安装 Pytorch以及openmmlab相关的环境

!pip3 install install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio==0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html

!pip install -U openmim

!mim install mmengine

!mim install 'mmcv==2.0.0rc3'

!mim install "mmdet>=3.0.0rc6"

!pip install opencv-python pillow matplotlib seaborn tqdm pycocotools -i https://pypi.tuna.tsinghua.edu.cn/simple

!git clone https://github.com/open-mmlab/mmpose.git -b tutorial2023

!mim install -e .

跟着子豪的教程测试了一下检测图片和视频的效果

multi-person image

预训练模型的效果很不错

接着下载子豪标注的耳朵数据集对模型进行训练和模型评估

重新训练目标检测

python tools/train.py data/rtmdet_tiny_ear.py

python tools/test.py data/rtmdet_tiny_ear.py work_dirs/rtmdet_tiny_ear/epoch_200.pth

LWZ9 3W9C $SN9$US32R42Q

重新训练关键点检测

python tools/train.py data/rtmpose-s-ear.py

python tools/test.py data/rtmpose-s-ear.py work_dirs/rtmpose-s-ear/epoch_300.pth

O`T%L(L25R _7M1OOL2IUX

我提供了自己拍摄的一段视频对训练后的模型进行检测

image

模型对耳朵的检测和关键点定位效果十分优秀

最后我提供我相关的训练数据以及检测结果供大家学习交流

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