Anal Friend Request.mp4 Accessprint(features.shape) The extracted features can be used for various downstream tasks such as video clustering, similarity search, classification, etc. # Load a pre-trained model model = torchvision.models.video.i3d_resnet50(pretrained=True) anal friend request.mp4 # Assuming 'video_path' is your video file video_path = 'anal friend request.mp4' video_tensor = video_to_tensor(video_path) print(features # Reshape for model video_tensor = video_tensor.unsqueeze(0) # Add batch dimension anal friend request.mp4 import torch import torch.nn as nn import torchvision import torchvision.transforms as transforms import cv2 |
print(features.shape) The extracted features can be used for various downstream tasks such as video clustering, similarity search, classification, etc.
# Load a pre-trained model model = torchvision.models.video.i3d_resnet50(pretrained=True)
# Assuming 'video_path' is your video file video_path = 'anal friend request.mp4' video_tensor = video_to_tensor(video_path)
# Reshape for model video_tensor = video_tensor.unsqueeze(0) # Add batch dimension
import torch import torch.nn as nn import torchvision import torchvision.transforms as transforms import cv2
© 2010-2022 "Форум Радиосхемы". All Rights Reserved Почта PDA |