Comments (1)
Hello,
It sounds like you're encountering an intriguing issue with your model's behavior between validation and prediction. Here are a couple of things you might want to check:
-
Ensure Consistency in Image Preprocessing: Sometimes, discrepancies in how images are preprocessed between training/validation and inference can lead to such issues. Make sure that the same transformations and normalizations are applied.
-
Check Confidence Thresholds: The
model.predict()
method might be using a higher confidence threshold by default compared to whatmodel.val()
used. Try lowering the confidence threshold in your predict call:results = model.predict('path/to/images', conf=0.25) # Adjust the confidence threshold
-
Model State: Ensure that the model is correctly loading the weights and is in evaluation mode during inference:
model = YOLO('
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