Tomo_4.mp4 -

plt.scatter(pca_features[:, 0], pca_features[:, 1]) plt.show() This example provides a basic framework for extracting deep features from a video and simple analysis. Depending on your specific requirements (e.g., video classification, anomaly detection), you might need to adjust the model, preprocessing, and analysis steps. Also, processing a video frame-by-frame can be computationally intensive and might not be suitable for real-time applications without optimization.

from tensorflow.keras.applications import VGG16 from tensorflow.keras.preprocessing import image from tensorflow.keras.applications.vgg16 import preprocess_input 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. and analysis steps. Also

pca = PCA(n_components=2) pca_features = pca.fit_transform(features) such as clustering

# Check if video file was opened successfully if not cap.isOpened(): print("Error opening video file")