Faster-RCNN

A Keras Implementation of Faster-RCNN using a Tensorflow Backend for Custom Object Detection.

This is a work-in-progress. As of now, only RPN training is feasible.

This implementation works only in the following environment.

1. Keras 2.2.4 with Tensorflow Backend.
2. Tensorflow 1.14.0.

Steps Involved in Creating a FRCNN Object-Detection Model

• Generating Region Proposals (RPN)
• Non-Maximum Suppression (NMS)
• ROI Pooling
• RCNN for Classification and Adjusting Bounding Box Regression Values

Training RPN

Use the following command to train the RPN.

python train_rpn.py --input_path serengeti --dataset_name serengeti --network vgg16 --n_epochs 5 --n_epoch_length 10

NOTE - I have attached as much explanation as possible in the code. Hopefully, its understandable. Cheerio.

TO-DO

• Data Augmentation
• Validation Data in RPN
• Non-Maximum Suppression
• ROI Pooling
• RCNN
• Support for Other Base Networks as Backbone