Mask_RCNN v2.0 已经发布

此版本更新内容包括:

This release includes updates to improve training and accuracy, and a new MS COCO trained model.

Remove unnecessary dropout layer Reduce anchor stride from 2 to 1 Increase ROI training mini batch to 200 per image Improve computing proposal positive:negative ratio Updated COCO training schedule Add --logs param to coco.py to set logging directory Bug Fix: exclude BN weights from L2 regularization Use mean (rather than sum) of L2 regularization for a smoother loss in TensorBoard Better compatibility with Python 2.7 The new MS COCO trained weights improve the accuracy compared to the previous weights. These are the evaluation results on the minival dataset:

Evaluate annotation type bbox Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.347 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.544 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.377 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.163 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.390 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.486 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.424 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.433 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.481 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.601 Evaluate annotation type segm Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.296 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.510 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.306 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.128 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.330 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.430 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.258 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.369 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.376 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.173 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.417 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.538 Big thanks to everyone who contributed to this repo. Names are in the commits history.

详情查看:https://gitee.com/XiaoGuil_Liu/Mask_RCNN/releases/v2.0

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