Anal Friend Request.mp4 -

# Reshape for model video_tensor = video_tensor.unsqueeze(0) # Add batch dimension

# Load video and extract frames def video_to_tensor(video_path): cap = cv2.VideoCapture(video_path) frames = [] while cap.isOpened(): ret, frame - cv2.read() if not ret: break frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) frame = transform(frame) frames.append(frame) cap.release() return torch.stack(frames) anal friend request.mp4

# 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

# Extract features with torch.no_grad(): features = model(video_tensor) anal friend request.mp4

print(features.shape) The extracted features can be used for various downstream tasks such as video clustering, similarity search, classification, etc.

import torch import torch.nn as nn import torchvision import torchvision.transforms as transforms import cv2

# Load a pre-trained model model = torchvision.models.video.i3d_resnet50(pretrained=True)