Keras-PANet

PANet for Instance Segmentation and Object Detection

This is an implementation of PANet on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet backbone.

Training on MS COCO

In this repository, i train the code with BN layers in the backbone fixed and use GN in other part. Training and evaluation code is in samples/coco/coco.py. You can run it directly from the command line as such:

# Train a new model starting from ImageNet weights
python3 samples/coco/coco.py train --dataset=/path/to/coco/ --model=/path/pretrained_models/resnet50.h5  --download=True

# Continue training the last model you trained. This will find
# the last trained weights in the model directory.
python3 samples/coco/coco.py train --dataset=/path/to/coco/ --model=last

You can also run the COCO evaluation code with:

# Run COCO evaluation on the last trained model
python3 samples/coco/coco.py evaluate --dataset=/path/to/coco/ --model=last

The training schedule, learning rate, and other parameters should be set in samples/coco/coco.py.

Reference

Original implementation[https://github.com/ShuLiu1993/PANet]

Mask RCNN[https://github.com/matterport/Mask_RCNN]