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.tiff files often contain multi-page images, layers, or high bit-depth channels. Azure Vision API may not normalize, flatten, or convert .tiff images the same way as it does with .jpg or .png. If the API processes only the first page or doesn't handle compression schemes like LZW or Deflate, the result may be distorted or misinterpreted.
JPEGs are uniformly RGB, 8-bit, single-frame, and they are easier for the model to process consistently. But TIFFs could be grayscale, CMYK, or RGBA, introducing variations in how the model extracts features.
Feeding models with .tiff might bypass or confuse normalization routines (e.g., resizing, color correction), leading to inconsistent vector generation.
Its recommended to convert all images into .jpg or .png before embedding.
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