# Load the video cap = cv2.VideoCapture('tomo_4.mp4')
# Extract features from all frames features = extract_features(frames) print(features.shape) The analysis depends on your specific goals, such as clustering, classification, or visualization. tomo_4.mp4
cap.release() For extracting features, you can use a pre-trained model like VGG16. We'll use TensorFlow/Keras for this. # Load the video cap = cv2
pca = PCA(n_components=2) pca_features = pca.fit_transform(features) such as clustering
from tensorflow.keras.applications import VGG16 from tensorflow.keras.preprocessing import image from tensorflow.keras.applications.vgg16 import preprocess_input
# Check if video file was opened successfully if not cap.isOpened(): print("Error opening video file")