A simple Mask-Cascade-RCNN implementation. Not perfect, only for learning and reference.
Paper:
The purpose of implementing this code is to comb the knowledge system of Mask-RCNN and Cascade-RCNN, and make the code readable and easy for others to learn.
Most implementations of Mask-RCNN are very complex and hard to read, and this repo, without the need for compilation and complex installation, is very handy. The code structure was a reference to Detectron2, and it was very easy to run on WINDOWS and LINUX.
- If you want to train this model, you can easily start by modifying
config.pyand usingpython train.py. - If you want to use trained weights, here is a checkpoint with only a simple train without tuning, but it's a little bit bigger (1.1gb, ResNet-101 as backbone). Note the modification of the checkpoint file path in the demo code.
- Refer to
demo.pyfor the test.
If you want to train your custom dataset, please refer here to write your own dataset code.
torch>=1.4
torchvision>=0.4
opencv-python==4.1.2.30
albumentations
pillow
timm
tensorboardX
easydict
fvcore
The dataset currently used is WGISD.
This is a small dataset, which is convenient for experiments.
The train curve
Result visualization
