ok, thanks for clarifying. I trained the model for 30 epochs. The average precision score is 0.56 for one class. The validation loss trended downwards the first few epochs and increased in between, but overall the loss continued to go down with each epoch. I did model inference using the predict method on an image (part of training set) and got the result below: Since the image was from the training data set, I expected that the result would be almost accurate. But, the detected results are very inaccurate. It detected the class everywhere but the actual weld. I don't understand why this is the case. Can you explain what could be the reason? Also, I trained the model on the same data set using YOLOv3 for 30 epochs. The model accuracy is 0.14, which is much less compared to the SSD.
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