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

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Can i know Write a function to extract feature embeddings from a pre-trained ResNet model for One-Shot Learning.
Apr 4 in Generative AI by Nidhi
• 16,020 points
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1 answer to this question.

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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.
answered Apr 9 by vashnavi

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