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After AI Localizes an Image Region: Align Cropping, Rotation and Coordinates
Image recognition results look skewed, and sometimes the problem comes from scaling and cropping rather than the model not finding the target. This article focuses on the application process of visual tasks, discusses the correspondence between original image coordinates, preprocessing records and display coordinates, and provides a visual regression method. The output area is only used for auxiliary inspection and cannot be directly used as a real size, identification or automatic operation authorization.
ChinaOPC Editorial TeamOriginal analysis1 min readChina2 views
Source timingPublic information and official documents; verified on October 23, 2026.
The Florence-2 documentation provides examples of regional vision tasks. The following is ChinaOPC's engineering analysis of the image processing link. The positioning accuracy of the model is not reported.
Record parameters for each transformation
Simulate a picture that is first cropped and then scaled, retaining the original size, cropping starting point, rotation angle and scaling ratio. When the result returns to the page display, it is converted according to the same link. The processed coordinates cannot be directly drawn on the original image.
Check the mapping with a manually labeled sample image
Prepare horizontal images, vertical images, edge target and multi-target samples, and overlay the results to see if the positions are consistent. If all boxes are offset in similar directions, check the coordinate logic first. Test records save input and preprocessed versions for easy reproduction.
Downstream actions are still verified separately
Correct location does not necessarily mean that the target category is correct. The application should allow manual correction and leave it in an unconfirmed state. When it comes to clicking or modifying system content, business permissions and objects must also be verified, and irreversible actions cannot be performed with just a visual box.
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