YgLK / ocular-disease-recognition

Multiclass classification of eye diseases based on eye fundus images using CNNs
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classification computer-vision convolutional-neural-networks deep-learning machine-learning

ocular-disease-recognition

Multiclass classification of eye diseases based on fundus images using CNN

Project content

No. Content Notebook
1 Initial data exploration and analysis. 01_eye_dis_detect.ipynb
2 Data preparation 02_data_preprocessing.ipynb
3 Multi-class classification on the whole dataset with simple augmentation 03_classification_attempt.ipynb
4 Binary-class classification: Normal vs Cataract 04_binary_classification.ipynb
5 Multi-class classification: Normal vs Cataract vs Myopia 05_multiclass_classification.ipynb
6 ConvNet filters analysis 06_filter_analysis.ipynb
7 Simple tool for image augmentation augmentor.ipynb

Summary

Content Notebook
Final model (Normal vs Cataract vs Myopia) model5_RGB_n10.h5
FINAL - whole project in one notebook (notebooks 1-6 included) ocular_disease_FINAL.ipynb
Project presentation project_presentation.pdf