We used mmdetection(mask rcnn) to train supervisely person dataset.
- Ubuntu 16.04
- Python 3.4+
- PyTorch 0.4.1
- Cython
git clone https://github.com/nicehuster/mmdetection-supervisely-person-datasets.git
cd mmdetection-supervisely-person-datasets
bash compile.sh
# run setup
python setup.py install
# or install locally
python setup.py install --user
export PYTHONPATH=$PYTHONPATH:{pwd}
You can download supervisely person dataset from the official website, after download the dataset, place it in data folder, and The dataset is structured as follows:
.
├── ds1
│ ├── ann
│ └── img
...
├── ds11
│ ├── ann
│ └── img
├── ds12
│ ├── ann
│ └── img
├── ds13
│ ├── ann
│ └── img
└── meta.json
You can download the pretrained model trained on supervisely person dataset in baidu,passwd:ytiv
python demox.py
python tools/train.py configs/supervisely.py --gpus 2
Important:
- you need to set the learning rate proportional to the GPU num. E.g., modify lr to 0.01 for 4 GPUs or 0.005 for 2 GPUs.
- In this repository, the pytorch version is 0.4.1
- In the pretrained model, I only trained the model 80 epoches, you can train more epoch to get better results.