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项目作者： sheldonsebastian

项目描述 ：
Image Classification to identify whether Red Blood Cells are infected with Malaria or not.
高级语言： Jupyter Notebook
项目地址: git://github.com/sheldonsebastian/Red-Blood-Cell-Classification.git


README

Final Report:

https://sheldonsebastian.github.io/Red-Blood-Cell-Classification/

Directory Structure:

Path Description
/POCs Files containing the proof of concepts/experimentation
/docs Files related to report website
/input Training image data and labels split into train, validation and holdout set
/src/common Common utility functions used by all scripts
/src/model_trainers Files containing code for training the model using:
1. manual hyperparameter tuning
2. random search hyperparameter tuning
3. Optuna (Automatic hyperparameter tuning)
/src/0_preprocess.py Code to preprocess the image files and split into train-validation-holdout splits
/src/1_eda.py Exploratory Data Analysis Jupyter Notebook
/src/2_inference.py Using the trained models make inference on validation and holdout set
requirements.txt List of all the packages used for this project

Steps to replicate project:

  1. Download repository
  2. To install all required python packages use: conda create —name rbc_classification —file requirements.txt
  3. Update BASE_DIR in src/0_manual.py, src/1_random_search.py, src/2_hyper_optimizer.py to current directory on your machine
  4. Run src/0_manual.py, src/1_random_search.py, src/2_hyper_optimizer.py to train models and save them in saved_models directory
  5. Run src/2_inference_holdout.py to perform inference on holdout(unseen) data.