Update README.md

README.md

@@ -37,6 +37,34 @@ This huggingface repository includes video storyboard classification models, fra
 </table>
 </div>
 
+##Video classification model
+
+   ```python
+   import torch
+   from PIL import Image
+   from model_loader import build_model
+
+   # Load the model
+   net = build_model(mode='classify')
+   model_path = 'Video storyboard classification models'
+
+   # Enable multi-GPU support
+   net = torch.nn.DataParallel(net)
+   torch.backends.cudnn.benchmark = True
+   state = torch.load(model_path, map_location=torch.device('cuda'))
+   net.load_state_dict(state['net'])
+   net.eval()
+
+   # Load the video storyboard and convert it to a PyTorch tensor
+   img_path = 'path/to/your/image.jpg'
+   img = Image.open(img_path)
+   img = img.resize((224, 224))
+   img_tensor = torch.tensor(np.array(img)).unsqueeze(0).to('cuda')
+
+   # Extract features from the image using the ResNet50 model
+   outputs = net(img_tensor)
+   ```
+
 The video processing pipeline leading to the clean videos in the Surg-3M dataset is as follows:
 <div align="center">
   <img src="https://cdn-uploads.huggingface.co/production/uploads/67d9504a41d31cc626fcecc8/yj2S0GMJm2C2AYwbr1p6G.png"> </img>