harleyzhang / Mobile_Mask_RCNN

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow for Mobile Deployment

Mobile Mask R-CNN

This is a Mask R-CNN implementation with MobileNet V1/V2 as Backbone architecture to be finally able to deploy it on mobile devices such as the Nvidia Jetson TX2.

Getting Started

• install required packages (mostly over pip)
• clone this repository
• download and setup the COCO Dataset: setup_coco.py
• inside coco.py subclass Config (defined in config.py) and change model params to your needs
• train mobile mask r-cnn on COCO with: train_coco.py
• evaluate your trained model with: eval_coco.py
• do both interactively with the notebook train_coco.ipynb
• if you face killed kernels due to memory errors, use bash train.sh for infinite training
• visualize / control training with tensorboard: cd into your current log dir and run:
  tensorboard --logdir="$(pwd)"
• inspect your model with notebooks/:
  inspect_data.ipynb,inspect_model.ipynb, inspect_weights.ipynb
• convert keras h5 to tensorflow .pb model file, in notebooks/ run:
  export_model.ipynb

Requirements

• numpy
• scipy
• Pillow
• cython
• matplotlib
• scikit-image
• tensorflow>=1.3.0
• keras>=2.1.5
• opencv-python
• h5py
• imgaug
• IPython[all]
• pycocotools

Original Matterport README