Different image inferences with same result

[arvisioncode]

Hi,

Im doing different tests with demo/clipiqa_single_image_demo.py and the attribute_list = ['Quality', 'Brightness', 'Sharpness', 'Noisiness', 'Colorfulness', 'Contrast'].

First, I’ve seen that fitting a good size to the input image is essential because in some cases the result is NaN. Is there a fixed size that should be adjusted in the inbound image?

In the tests I’m doing, regardless of the resize, I see that it doesn’t matter the input image the result is always the same, you know what might be?

Example:

MSI@DESKTOP-FEG9P7H MINGW64 /e/2. Projects/Image Quality/CLIP-IQA (v2-3.8)
$ python demo/clipiqa_single_image_demo.py --config configs/clipiqa/clipiqa_attribute_test.py --file_path dataset/good_1.jpg 
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
['Quality', 'Brightness', 'Sharpness', 'Noisiness', 'Colorfulness', 'Contrast', 'Quality']
[0.9892578  0.98876953 0.99853516 0.06512451 0.74316406 0.66796875]
(clipiqa) 
MSI@DESKTOP-FEG9P7H MINGW64 /e/2. Projects/Image Quality/CLIP-IQA (v2-3.8)
$ python demo/clipiqa_single_image_demo.py --config configs/clipiqa/clipiqa_attribute_test.py --file_path dataset/bad_3.jpeg 
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
['Quality', 'Brightness', 'Sharpness', 'Noisiness', 'Colorfulness', 'Contrast', 'Quality']
[0.9892578  0.98876953 0.99853516 0.06512451 0.74316406 0.66796875]
(clipiqa) 
MSI@DESKTOP-FEG9P7H MINGW64 /e/2. Projects/Image Quality/CLIP-IQA (v2-3.8)
$ python demo/clipiqa_single_image_demo.py --config configs/clipiqa/clipiqa_attribute_test.py --file_path dataset/blur_2.tif
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
['Quality', 'Brightness', 'Sharpness', 'Noisiness', 'Colorfulness', 'Contrast', 'Quality']
[0.9892578  0.98876953 0.99853516 0.06512451 0.74316406 0.66796875]
(clipiqa)