├── CNN_combined.ipynb ├── GLAUCOMA DETECTION USING DEEP LEARNING.pptx ├── Glaucoma detection using cnn.pdf ├── Glaucoma detector web app.mp4 ├── LICENSE └── README.md /GLAUCOMA DETECTION USING DEEP LEARNING.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SaiHitesh16/Glaucoma-Detection-using-CNN/d70b46fea4ca74b4a03d700046b8836ac46b44b9/GLAUCOMA DETECTION USING DEEP LEARNING.pptx -------------------------------------------------------------------------------- /Glaucoma detection using cnn.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SaiHitesh16/Glaucoma-Detection-using-CNN/d70b46fea4ca74b4a03d700046b8836ac46b44b9/Glaucoma detection using cnn.pdf -------------------------------------------------------------------------------- /Glaucoma detector web app.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SaiHitesh16/Glaucoma-Detection-using-CNN/d70b46fea4ca74b4a03d700046b8836ac46b44b9/Glaucoma detector web app.mp4 -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2023 SaiHitesh16 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Glaucoma-Detection-using-CNN [![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://glaucoma-detector.streamlit.app) 2 | 3 | Link: https://glaucoma-detector.streamlit.app 4 | 5 | A deep learning-based glaucoma detection method is being developed in this project. Convolutional neural networks (CNNs), which are trained using publically accessible datasets of fundus images of healthy and glaucomatous eyes, are used in this system to classify images. 6 | 7 | ## Details 8 | * Step 1:-In this project, we have collected three publicly available datasets namely ACRIMA,DRISTHI-GS amd RIM-ONE. 9 | * Step 2:-We have combined the three datasets to form a Combined dataset. 10 | * Step 3:-Data Augumentation is applied to Combined dataset in order to increase training data and boost the model's performance. 11 | * Step 4:-The combined dataset is split into training, testing, and validation data. 12 | * Step 5:-A Keras CNN model was built and trained using training data. 13 | * Step 6:-The model was evaluated using test data and metrics including accuracy (98%) and precision , recall , and F1-score . For future use, we saved the model file in h5 format. 14 | * Step 7:-Then we built a simple streamlit app for hosting on web. 15 | 16 | ## Requirements 17 | To run this project, you need to have the following software installed: 18 | * Python 3.8 19 | * Tensorflow 2.12.0 20 | * keras 2.12.0 21 | * plotly-express 0.4.1 22 | * numpy 1.22.4 23 | * pandas 1.5.3 24 | * streamlit 1.21.0 25 | * streamlit_ext 0.1.7 26 | 27 | You can install these packages using pip, by running the following command: 28 | pip install tensorflow keras streamlit 29 | 30 | ## Usage 31 | To use our project - go to this link https://glaucoma-detector.streamlit.app 32 | 33 | * The web app opens up in a new tab. Then you can use it for classifying. That's it! 34 | 35 | * Upload a (jpg,png,jpeg) fundus image/images of eye. Our model predicts whether affected by glaucoma or not. 36 | 37 | ## License 38 | [MIT LICENSE](https://github.com/SaiHitesh16/Glaucoma-Detection-using-CNN/blob/main/LICENSE) 39 | --------------------------------------------------------------------------------