TannerGilbert / Object-Detection-and-Image-Segmentation-with-Detectron2

Object Detection and Image Segmentation with Detectron2
https://gilberttanner.com/blog/detectron-2-object-detection-with-pytorch
MIT License
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the result i trained is so bad! #8

Closed Yaoxingtian closed 3 years ago

Yaoxingtian commented 3 years ago

hello, thanks for your open resource! and i tried to train by the new datasets you provided, and the code you gave, but i cannot get the same result as you did, so confused about this, do you know what's the problems, if you can help ,so much appreciate !

Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.017 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.047 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.012 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.001 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.038 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.018 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.174 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.202 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.012 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.330

TannerGilbert commented 3 years ago

Hard to say. In general I didn't experience any training problems with Detectron2. What dataset are you training on?

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