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This article will explain in detail how to parse Mask R-CNN object detection and segmentation of Keras and TensorFlow code, the quality of the article content is high, so Xiaobian share for everyone to make a reference, I hope you have a certain understanding of related knowledge after reading this article.

Mask R-CNN Target Detection and Object Segmentation Keras and TensorFlow Implementation Code

This implementation is based on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each object instance in the picture. Feature Pyramid Network (FPN) and the backbone of ResNet101.

This giuhub repository contains the following:

Mask R-CNN source code built on FPN and ResNet101

Training code on MS COCO

Pre-trained weights on MS COCO

Jupyter notebooks visualizing each step of the pipline

Parallel classes for multi-GPU training

Indicator evaluation on MS COCO

Examples of training on your own dataset

The source code is annotated and designed to be easily extensible. If you use this code in your research, please refer to this repository. If you work in 3D vision, you might find our recently released Matterport3D dataset useful for you.

Keras and TensorFlow code on how to parse Mask R-CNN object detection and segmentation is shared here. I hope the above content can be helpful to everyone and learn more. If you think the article is good, you can share it so that more people can see it.

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