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# MMPose | ||
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Update: 2023/07/31 | ||
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## Info | ||
- Document: [readthedocs.io](https://mmpose.readthedocs.io/en/latest/overview.html) | ||
- Release: 2020 | ||
- Implementation: [open-mmlab/mmpose](https://github.com/open-mmlab/mmpose) | ||
- framework: Pytorch | ||
- License: Apache License 2.0 | ||
- Keywords: CV, RGB Image, Pose Estimation | ||
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## How to build with docker and run the model in a docker container | ||
This documentation describes the Pytorch version. The docker environment is as follows: | ||
- CPU: Intel® Core™ i9-9900K CPU @ 3.60GHz × 16 | ||
- GPU: NVIDIA GeForce RTX 2080 Ti | ||
- Memory: 64 GiB | ||
- Capacity: 1 TB | ||
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### 1. Create a docker container | ||
```bash | ||
# Set this repository absolute path (ex: /home/user/obarads.github.io) | ||
git clone https://github.com/Obarads/obarads.github.io.git | ||
cd obarads.github.io | ||
OGI_DIR_PATH=$PWD | ||
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# Get a base image | ||
BASE_IMAGE=nvidia/cuda:11.7.1-cudnn8-devel-ubuntu20.04 | ||
docker pull $BASE_IMAGE | ||
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# Clone the repository | ||
git clone https://github.com/open-mmlab/mmpose.git | ||
# Move to text2room | ||
cd mmpose | ||
# Switch to 2023/07/04 ver. | ||
git switch -d 537bd8e543ab463fb55120d5caaa1ae22d6aaf06 | ||
# Copy a folder for building env. | ||
cp -r $OGI_DIR_PATH/environments/mmpose/ ./dev_env | ||
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# Create docker image and container | ||
docker build . -t mmpose -f ./dev_env/Dockerfile --build-arg UID=$(id -u) --build-arg GID=$(id -g) --build-arg BASE_IMAGE=$BASE_IMAGE | ||
docker run -dit --name mmpose --gpus all -v $PWD:/workspace mmpose | ||
``` | ||
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### 2. Setup in the docker container | ||
In a docker container: | ||
```bash | ||
cd /workspace | ||
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# setup python and packages | ||
conda create -n mmpose python=3.10 | ||
conda activate mmpose | ||
cd dev_env | ||
pip install -r requirements.txt | ||
``` | ||
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### 3. Run the model | ||
Please open `/workspace/demo/MMPose_Tutorial.ipynb`, in the container and run the cells in `MMPose_Tutorial.ipynb`. |
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