EfficientDet.Pytorch
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Training results in detections at all anchorboxes
After training on the VOC2007 dataset with default options except epochs=5, and efficientdet-d2, I am getting detections of all classes at all anchorboxes when using both eval.py and demo.py. Changing thresholds to 0.99+ does not curb the detections.
I get the same result when training with a very tiny dataset with fewer epochs. Additionally my validation mAP is always 0, even when I evaluate on the training set.
I am using Luke Melas's backbone as suggested in this issue#111.
- Relevant packages in my conda environment are:
-
Name Version Build Channel
- albumentations == 0.4.5 == pypi_0 pypi
- cudatoolkit == 10.1.243 == h6bb024c_0
- numpy == 1.18.1 == py38h4f9e942_0
- numpy-base == 1.18.1 == py38hde5b4d6_1
- opencv-contrib-python == 4.2.0.32 == pypi_0 pypi
- pytoan == 0.6.4 == pypi_0 pypi
- pytorch == 1.4.0 == py3.8_cuda10.1.243_cudnn7.6.3_0 pytorch
- torchvision == 0.5.0 == py38_cu101 pytorch
Here is the output for python demo.py --cam -w=./saved/weights/VOC/efficientdet-d2/checkpoint_5.pth -t=.999 -it=.999
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