Inspired from Mask R-CNN to build a multi-task learning, two-branch architecture: one branch based on YOLOv2 for object detection, the other branch for instance segmentation. Simply tested on Rice and Shapes. MobileNet supported.
myolo
- the main implementation of Mask-YOLO. model.py is the model instantiation.
example
- including three training examples with inference: Shapes dataset is randomly generated by dataset_shapes.py. Rice and Food are small datasets I hand-annotated by VGG Image Annotator (VIA), and can be downloaded from https://drive.google.com/file/d/1druK4Kgx5AhfchClU2aq5kf7UVoDtkvu/view.