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app.py

@@ -1,5 +1,3 @@
-from IPython.display import clear_output, Image
-import argparse
 import numpy as np
 import random
 from PIL import Image
@@ -12,7 +10,7 @@ import torchvision.transforms as transforms
 from PIL import Image
 
 evice = torch.device('cpu')
-model = tag2text(pretrained='/content/recognize-anything/tag2text.pth', image_size=384, vit='swin_b')
+model = tag2text(pretrained='tag2text.pth', image_size=384, vit='swin_b')
 model.threshold = 0.68
 model.eval()
 

requirements.txt

@@ -1,5 +1,5 @@
 timm==0.4.12
-transformers==4.15.0
+transformers
 fairscale==0.4.4
 pycocoevalcap
 torch