Was facing an issue in classification model trained on fastai’s timm library (convnext model).
I was running images in batches on a classification model for batch inference. But due to 1 image, entire batch is failing. The classification model when trained was trained on preprocessed images, by applying transformations on image size = 224.
When the particular image is passed for inference, it shows this error and entire batch fails.
“Image size (191720704 pixels) exceeds limit of 178956970 pixels, could be decompression bomb DOS attack.”
Why is this error showing then?
Had preprocessed the images when I trained the model, by providing image size to be 224.
I’d like to respect the limit and not increase the limit (as described here: Pillow in Python won’t let me open image (“exceeds limit”))
How can I load it in a way that the resolution is lowered just below the limit and the lower resolution image is referenced in img without causing any error.
It’d be great to have a Python solution but if not, any other solution will work too.