Write a function to extract feature embeddings from a pre-trained ResNet model for One-Shot Learning

Question

Can i know Write a function to extract feature embeddings from a pre-trained ResNet model for One-Shot Learning.

Answer 1

Feature embeddings from a pre-trained ResNet model capture high-level representations crucial for One-Shot Learning comparisons.

Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Uses resnet18 as a feature extractor by removing the classification head.

• Applies standard ImageNet preprocessing for input normalization.

• Extracts and flattens a 512-dim embedding vector from input images.

Hence, leveraging ResNet's feature embeddings enables effective representation learning for One-Shot animal classification tasks.