Download: Video5179512026745012956.mp4 (5.75 Mb) -

This results in a vector (e.g., size 2048 for ResNet-50).

You can average the vectors from all sampled frames (Global Average Pooling) to create one unique "fingerprint" for the entire file. 5. Implementation (Python Snippet) Download: video5179512026745012956.mp4 (5.75 MB)

Instead of the final classification layer (which would say "dog" or "running"), you extract the output from the (often called the "bottleneck" or "pooling layer"). This results in a vector (e

Subtract the mean and divide by the standard deviation (specific to the dataset the model was trained on). This results in a vector (e.g.

Convert the images into numerical arrays (tensors). 4. Extract the Global Feature Vector

Use ResNet-50 or ViT (Vision Transformer) pre-trained on ImageNet.