FashionBert - Generate image features

Why does the image_feature_extract.py code for patch feature generation uses `num_patches = (4, 4)` at line 475? shouldn't it be (8,8)?

Also the paper states that patch features are generated using resnext101 while the script you give uses resnet 50, what is the correct one?

I'm asking because I did some experiments and i tried to generate features from the fashiongen validation dataset using your `image_feature_extract.py` code and i get strange results: given a certain product, the features i get for its image does not match with the features that you have in the csv evalution files. Maybe there is some preprocessing to do to images? The fashion gen validation dataset has 256x256 RGB images, are these the correct sizes?

I'm using this this code to extract features:
```python
feature_extractor = PatchFeatureExtractor("/content/resnet_v1_50")
results_batch = feature_extractor.predict([img], batch_size=1)
feature = results_batch[0]['feature']
```

Thank you for our help

Start with image_feature_extract.py around line 475 and the PatchFeatureExtractor usage shown in the issue. Compare its output for the FashionGen validation images with the CSV evaluation features, checking the stated ResNet model, patch dimensions, image size, and preprocessing. Done means the correct feature-generation settings are documented and produce matching validation features.

Written by the indexing model from the issue text.