The attention mechanism in a neural network can generate heatmaps by highlighting important regions in the input image, aiding in interpretability and focus.
Here is the code snippet you can refer to:


In the above code, we are using the following key points:
- Applies attention over CNN feature maps, creating an interpretable heatmap.
- Uses a softmax-normalized attention mask, highlighting important regions.
- Extracts global features via pooling, aiding in classification.
- Visualizes heatmaps using Matplotlib, showcasing model attention on input.
Hence, the attention mechanism enables heatmap generation by highlighting essential image regions, improving interpretability and aiding in Optical Character Recognition (OCR).