HaDR: Applying Domain Randomization for Generating Synthetic Multimodal Dataset for Hand Instance Segmentation in Cluttered Industrial Environments
- Linux (Windows is not officially supported)
- Python 3.5+
- PyTorch 1.1 or higher (>=1.5 is not tested)
- CUDA 9.0 or higher
- NCCL 2
- GCC 4.9 or higher
- mmcv 0.2.16
a. Create a conda virtual environment and activate it.
conda create -n mmdet python=3.7 -y
conda activate mmdet
b. Install PyTorch and torchvision following the official instructions, e.g.,
conda install pytorch torchvision -c pytorch
c. Clone the repository.
git clone https://github.com/anion0278/HaDR.git
cd HaDRd. Install build requirements and then install.
pip install -r requirements/build.txt
pip install "git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI"
pip install -v -e . # or "python setup.py develop"The dataset and pretrained SOLOv2 and Mask R-CNN models can be found on Kaggle.