Create app.py

app.py

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+import cv2, torch 
+import gradio as gr
+import numpy as np 
+import torchvision.models as models 
+from torchvision import transforms as T
+
+new_model = models.resnet18()
+num_ftrs = new_model.fc.in_features 
+new_model.fc = nn.Linear(num_ftrs, 75)
+checkpoint = torch.load('model_best_checkpoint.pth.tar')
+new_model.load_state_dict(checkpoint['model'])
+new_model.to(device)
+
+
+
+
+
+