https://github.com/adi3042/chest-x-ray-disease_detection_using_cnn
🩺 Chest X-Ray Disease Detection using CNN | Detect diseases from X-ray images with AI 📊🚀 | Features: Preprocessing, CNN architecture, accuracy metrics 💡 | Get Started: Clone & explore! 🖥️✨
https://github.com/adi3042/chest-x-ray-disease_detection_using_cnn
chest-xray-images classification cnn-classification deployment disease-detection keras-tensorflow mobilenet model-selection models neural-networks
Last synced: 6 months ago
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🩺 Chest X-Ray Disease Detection using CNN | Detect diseases from X-ray images with AI 📊🚀 | Features: Preprocessing, CNN architecture, accuracy metrics 💡 | Get Started: Clone & explore! 🖥️✨
- Host: GitHub
- URL: https://github.com/adi3042/chest-x-ray-disease_detection_using_cnn
- Owner: Adi3042
- License: mit
- Created: 2024-10-19T22:36:12.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-12-09T17:38:46.000Z (10 months ago)
- Last Synced: 2025-02-09T10:14:16.407Z (8 months ago)
- Topics: chest-xray-images, classification, cnn-classification, deployment, disease-detection, keras-tensorflow, mobilenet, model-selection, models, neural-networks
- Language: Jupyter Notebook
- Homepage: https://adi3042.github.io/Chest-X-Ray-Disease_Detection_using_CNN/
- Size: 159 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🌟 Chest X-Ray Disease Detection using CNN 🩺
This project focuses on utilizing **Convolutional Neural Networks (CNN)** for the **detection of Pneumonia** from chest X-ray images. The goal is to assist in faster and more accurate diagnoses, contributing to better medical decision-making.
## 🚀 Features
✨ **Data Preprocessing**: Efficient cleaning and preparation of X-ray images.
📊 **Model Training**: CNN-based model to classify chest X-rays.
📈 **Evaluation**: Performance metrics like accuracy, loss, and confusion matrix.
📸 **Visualization**: Easy visualization of X-rays and model predictions.
## 🛠️ Installation
1. **Clone the repository**:
```bash
git clone https://github.com/Adi3042/Chest-X-Ray-Disease_Detection_using_CNN.git
```
2. **Navigate to the project directory**:
```bash
cd Chest-X-Ray-Disease_Detection_using_CNN
```
3. **Install dependencies**:
```bash
pip install -r requirements.txt
```
4. **Run app.py**:
```bash
python app.py
```
5. **Visit at Given link**:
```bash
http://127.0.0.1:5000/
```
## 🧑💻 Usage
1. **Download the dataset** from [Kaggle](https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia).
2. **Prepare the dataset**:
- Extract the dataset into the `chest_xray` folder.
- Merge all images from `train`, `test`, and `val` folders:
- Move all **NORMAL** images into a single `NORMAL/` folder.
- Move all **PNEUMONIA** images into a single `PNEUMONIA/` folder.
- Ensure your structure looks like this:
```
Chest-X-Ray-Disease_Detection_using_CNN/
├── data/
│ ├── NORMAL/
│ ├── PNEUMONIA/
├── saved_models/
│ ├── Chest_Disease_Classifier_Model.h5
│ ├── Chest_Disease_Classifier_Model.keras
│ ├── Chest_Disease_Classifier_Model.tflite
├── src/
│ ├── exception.py
│ ├── logger.py
│ ├── utils.py
├── static/
│ ├── javascript/
│ │ ├── index.js
│ │ ├── contactUs.js
│ ├── css/
│ │ ├── index.css
│ │ ├── contactUs.css
│ ├── assets/
│ │ ├── chest.png
│ │ ├── favicon.png
│ │ ├── logo1.png
├── templates/
│ ├── index.html
│ ├── contactUs.html
├── app.py
├── Chest_X_Ray.ipynb
├── requirements.txt
├── LICENSE
├── .gitignore
```
## 📜 License
This project is licensed under the **MIT License**. See the [LICENSE](LICENSE) file for more details.