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Image classification with CNN_classifier, MLOPS end to end project

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sh3rin3j3sna/Fowl_disease_identification

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Fowl_disease_identification

Image classification with CNN_classifier

End-to-end MLOPS project design (DVC)

*image classification *MLOPS

Inspired by krishnaik videos on end-to-end ML projects.

The project workflow is as follows

  1. Project Template creation
  2. Project setup requirements and installations
  3. Logging, Utils and Exception
  4. All components on Notebook Experiments
  5. All components Modular code implementation
  6. Training pipeline
  7. DVC tool - for Pipeline Tracking and Implementation
  8. Prediction pipeline
  9. Docker
  10. Final CI/CD deployment (AWS and Azure)

About the project

The project motivation is classifying fowl with coccidiosis through image analysis.The classifier used is CNN.

Some sneak peak to the fowl disease.

Coccidiosis is caused by parasites that infect the cells lining an animal’s intestine. Animals get infected by swallowing the parasites. This can happen by eating infected pasture and feed, drinking contaminated water, or by grooming themselves.

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Image classification with CNN_classifier, MLOPS end to end project

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