Ugenteraan/ResNet-50-CBAM-PyTorch

Implementation of Resnet-50 with and without CBAM in PyTorch v1.8. Implementation tested on Intel Image Classification dataset from https://www.kaggle.com/puneet6060/intel-image-classification.

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This helps deep learning engineers train and evaluate image classification models more effectively. You provide a dataset of categorized images, and it outputs a trained model ready to classify new images, potentially with improved accuracy by using the CBAM attention mechanism. This tool is for machine learning practitioners focused on computer vision tasks.

100 stars. No commits in the last 6 months.

Use this if you are a deep learning engineer needing a pre-built ResNet-50 architecture to classify images, especially if you want to experiment with or leverage a CBAM attention module for better performance.

Not ideal if you are a business user looking for a no-code image classification solution or if you need to classify non-image data.

Image Classification Computer Vision Deep Learning Model Training Attention Mechanisms Neural Network Architecture
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 20 / 25

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Stars

100

Forks

23

Language

Python

License

MIT

Last pushed

Jan 11, 2022

Commits (30d)

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