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this is when using custom dataset with nonuniform image sizes
File "/home/xiangyong/Workbench/RetinaNet-unsky/retinanet/core/metric.py", line 73, in update cls_loss = np.sum(-1 * alpha * labels * np.power(1 - cls_+eps, gamma) * np.log(cls_+eps) - (1-labels)*(1-alpha) * np.power(1 - ( 1-cls_)+eps, gamma) * np.log( 1-cls_+eps)) ValueError: operands could not be broadcast together with shapes (1,20,123) (1,5,123)
The text was updated successfully, but these errors were encountered:
Have you changed your num_classes variable to the number of your custom dataset? You need to change it in both pascal_voc.py file and metric.py file.
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this is when using custom dataset with nonuniform image sizes
File "/home/xiangyong/Workbench/RetinaNet-unsky/retinanet/core/metric.py", line 73, in update
cls_loss = np.sum(-1 * alpha * labels * np.power(1 - cls_+eps, gamma) * np.log(cls_+eps) - (1-labels)*(1-alpha) * np.power(1 - ( 1-cls_)+eps, gamma) * np.log( 1-cls_+eps))
ValueError: operands could not be broadcast together with shapes (1,20,123) (1,5,123)
The text was updated successfully, but these errors were encountered: