Chizuru-Kagura / keras-rpn

Region Proposal Network implementation for object detection using Keras and TensorFlow

keras-rpn

Region Proposal Network implementation for object detection using Keras and TensorFlow

This repository was heavily based on the Mask-RCNN repository (https://github.com/matterport/Mask_RCNN).

Getting Started

Dependencies

This was developed using Windows 10 Pro with the following dependencies:

• Keras 2.2.4
• tensorflow-gpu 1.12.0
• numpy 1.15.4
• matplotlib 3.0.2
• CUDA 9.0
• cuDNN v6.0
• Python 3.6.5

Other versions of these dependencies are not guaranteed to work.

Example Scripts

2018 Data Science Bowl

1. Download the data from the nuclei dataset from https://www.kaggle.com/c/data-science-bowl-2018/data and extract to a folder of your choice.
2. Change the stage1_train folder name to train.
3. Create a new folder validation and drag however many samples you'd like for validation from train into validation.
4. Change the TRAIN_PATH and VALIDATION_PATH variables in the nucleus/train.py script to where the train and validation folders are located.
5. Run python nucleus/train.py from the command line.