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PaddleOCR generally performs best when the input image is in RGB format, as the models are typically trained and fine-tuned on RGB images. The inconsistency you observed between BGR and grayscale inputs is likely due to the fact that the model's training data and preprocessing pipelines are configured for RGB images. Here are some key points to address your question:
Recommendation:To ensure the best performance and consistency:
Additional Reference:You can refer to the discussion on the official PaddleOCR GitHub repository here, where it's confirmed that PaddleOCR expects images in RGB format. Response generated by feifei-bot | chatgpt-4o-latest |
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I have noticed that processing the same image on different channels returns different results. I did not test it out with more images but I passed a BGR image and it was recognized correctly. However, the model misclassified the same image when converted to grayscale. So, is there a fixed preferred channel/ config to get better results? (Grayscale/ BGR/ RGB)
Model : Finetuned en_PP-OCRv4_rec
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