maskrcnn-pytorch

(Currently, this project is under fast update state, will be fully available very soon.)

Mask R-CNN implementation in PyTorch

Usage

(Will be available very soon.)

from maskrcnn import MaskRCNN

mask_rcnn = MaskRCNN(num_classes=1000)

def train():
    pass
def predict():
    pass

Source directory explain

1. backbone:

Several backbone models support Mask R-CNN, like ResNet-101-FPN.

2. proposal:

RoI(Region of Interest) Proposal, like RPN and variants.

3. pooling:

Pooling for fixed dimensional representation, like RoIAlign and some variants.

4. head:

Predict heads include classification head, bounding box head, mask head and their variants.

5. lib:

Some third-party lib this project based on.

Reference:

1. Kaiming He et al. Mask R-CNN
2. Shaoqing Ren et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
3. rbgirshick/py-faster-rcnn
4. ruotianluo/pytorch-faster-rcnn
5. TuSimple/mx-maskrcnn
6. matterport/Mask_RCNN