Da (3).mp4 < EXCLUSIVE | 2026 >

# Get features with torch.no_grad(): features = model(tensor_frame)

# Read video video_capture = cv2.VideoCapture('da (3).mp4') da (3).mp4

# Transform to apply to frames transform = transforms.Compose([ transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) ]) # Get features with torch

# Move to GPU if available device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') tensor_frame = tensor_frame.to(device) model.to(device) da (3).mp4

# Load a pre-trained model model = torchvision.models.resnet50(pretrained=True) model.eval() # Set to evaluation mode

# Add batch dimension tensor_frame = tensor_frame.unsqueeze(0)