Hello, I think I am having weird results like mAP=1.0 after the first epoch and wanted to be sure if the model works so well on my custom dataset. But I don't know how to analyse the outputs coming from the model. Apart from outputs1, outputs2, out3 variables, only outputs is returned as model final predictions; and all the values are negative. Since its sigmoid I was thinking to print the labels having > 0 prediction, but it doesn't seem to work because everything is negative. How should we use the
outputs = self.on_forward(inputs, targets, is_train=is_train)
line in trainer.py to print or plot the predicted labels for the given image?
I add an example screenshot to show the output vector I get for batch size = 4 (while mAP is always 1.0)
Hello, I think I am having weird results like mAP=1.0 after the first epoch and wanted to be sure if the model works so well on my custom dataset. But I don't know how to analyse the outputs coming from the model. Apart from outputs1, outputs2, out3 variables, only outputs is returned as model final predictions; and all the values are negative. Since its sigmoid I was thinking to print the labels having > 0 prediction, but it doesn't seem to work because everything is negative. How should we use the
outputs = self.on_forward(inputs, targets, is_train=is_train)line in trainer.py to print or plot the predicted labels for the given image?
I add an example screenshot to show the output vector I get for batch size = 4 (while mAP is always 1.0)