Mask R-CNN for Object Detection and Segmentation

This is an implementation of Mask R-CNN 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 ResNet101 backbone.

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use cpu ,epochs 5

Getting Started

1.Environment

Windows/Linux + Keras >= 2.0.8 + TensorFlow >= 1.3.0
pip install -r requirements.txt

2.Custom Train Data

pip install labelme
labelme
mkdir train_data
train_data
    |-json
    |-labelme_json
    |-pic
    |-cv2_mask

• Details:(https://www.cnblogs.com/houyong/p/10266228.html)

3.Download pre-trained weights

mask_rcnn_coco.h5

• BaiDuYun:https://pan.baidu.com/s/1CmcfVleyw7QpVZRo3JxS2w code:tf7f

4.Train

python train_shape.py

5.Test

python test_shape.py