Fix Inconsistency Between Training and Inference Caused by Multi-Scale Input Handling for Rectangular Inputs. #422
+11
−2
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Problem:
Inconsistency issues identified between the training and inference phases related to how multi-scale inputs are handled.
Details:
During training, if the input image's height does not equal its width, our multi-scale process adjusts the image to be square. However, during inference, the inputs are maintained as rectangles. This inconsistency has led to a substantial degradation in model performance, with a decrease in mean Average Precision (mAP) by approximately 20% on our company's datasets.
Modifications: