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Garbage classification website on AWS with Tensorflow ResNet50 as deeplearning model, FastAPI as backend and ReactJs as frontend.

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thangbuiq/garbage-classification-web

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Machine Learning To Production

Important

Our project during the university course, we have deployed a webapp to classify garbage images. We have used ResNet50 model to classify the images. The model has been trained on the dataset of 6 classes: cardboard, glass, metal, paper, plastic, trash. The model has achieved 90% accuracy on the test set. You can see the proof at our report. But because of the cost, we have to stop the service. So, we choose Render to deploy our webapp and change the model to Zero-shot learning instead of ResNet50.

Note

View our webapp at => garbage-classification-web.vercel.app

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    Architecture Diagram

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