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Pneumonia Detection using X-Ray Images
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diff --git a/Pneumonia Detection using X-Ray Images/Dataset/Readme.md b/Pneumonia Detection using X-Ray Images/Dataset/Readme.md
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+# Pneumonia Detection using X-Ray images
+## Detaset link: https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia
diff --git a/Pneumonia Detection using X-Ray Images/Images/Accuracy Graph CNN.png b/Pneumonia Detection using X-Ray Images/Images/Accuracy Graph CNN.png
diff --git a/Pneumonia Detection using X-Ray Images/Images/Accuracy Graph Efficientnet50.png b/Pneumonia Detection using X-Ray Images/Images/Accuracy Graph Efficientnet50.png
diff --git a/Pneumonia Detection using X-Ray Images/Images/CNN Result.png b/Pneumonia Detection using X-Ray Images/Images/CNN Result.png
diff --git a/Pneumonia Detection using X-Ray Images/Images/Grayscale visuals.png b/Pneumonia Detection using X-Ray Images/Images/Grayscale visuals.png
diff --git a/Pneumonia Detection using X-Ray Images/Images/Loss Graph CNN.png b/Pneumonia Detection using X-Ray Images/Images/Loss Graph CNN.png
diff --git a/Pneumonia Detection using X-Ray Images/Images/Loss Graph EfficientNet50.png b/Pneumonia Detection using X-Ray Images/Images/Loss Graph EfficientNet50.png
diff --git a/Pneumonia Detection using X-Ray Images/Images/Matshow Image.png b/Pneumonia Detection using X-Ray Images/Images/Matshow Image.png
diff --git a/Pneumonia Detection using X-Ray Images/Models/Pneumonia Detection using X-Ray Images.ipynb b/Pneumonia Detection using X-Ray Images/Models/Pneumonia Detection using X-Ray Images.ipynb
diff --git a/Pneumonia Detection using X-Ray Images/Models/Pneumonia Detection via CNN.ipynb b/Pneumonia Detection using X-Ray Images/Models/Pneumonia Detection via CNN.ipynb
diff --git a/Pneumonia Detection using X-Ray Images/Readme.md b/Pneumonia Detection using X-Ray Images/Readme.md
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+# <p align = "center">Pneumonia Detection using X-Ray images </p>
+## <p align = "center">Aim of the project: To detect the pneumonica of the patient using the X-Ray images dataset.</p>
+## Libraries and Frameworks used:
+#### 1. Pandas
+#### 2. Numpy
+#### 3. Matplotlib
+#### 4. Tensorflow
+#### 5. Keras
+#### 6. OpenCV
+#### 7. Imutils
+#### 8. Pathlib
+
+## Deep Learning Algotithms used:
+#### 1. EfficientNet50
+#### 2. MobileNetV2
+#### 3. InceptionV3
+#### 4. Normal Convolutional Neural Network
+
+## Evaluation Metrics used:
+#### 1. Mean Absolute Error
+
+## Loss Functions Used:
+#### 1. Softmax 
+#### 2. Rectified Linear Unit
+
+## <p align = "center">Images</p>
+
+
+
+### <p align = "center">Visualization Phase using Matplotlib</p>
+
+![Grayscale visuals](https://github.com/PiyushBL45t/DL-Simplified/assets/75735209/72b48b73-0e39-45a1-a42a-573ba954f99e)
+
+
+![Matshow Image](https://github.com/PiyushBL45t/DL-Simplified/assets/75735209/5b8751c5-3584-4d60-b181-875735236d97)
+
+
+
+
+
+## Loss and Accuracy Statistics
+<p align = "center">Loss and Accuracy Graphs for EfficientNEt50 Algorithm</p>
+
+#### Loss Graph
+![Loss Graph EfficientNet50](https://github.com/PiyushBL45t/DL-Simplified/assets/75735209/69e94b4e-5b48-4a3d-a340-d92d72441534)
+
+#### Accuracy Graph
+![Accuracy Graph Efficientnet50](https://github.com/PiyushBL45t/DL-Simplified/assets/75735209/8a86826b-5dff-4e84-b679-092ecb122f70)
+
+
+<p align = "center">Loss and Accuracy Graphs for CNN Algorithm</p>
+
+#### Loss Graph
+
+![Loss Graph CNN](https://github.com/PiyushBL45t/DL-Simplified/assets/75735209/23a28c42-5abe-4e29-9837-7e487f07b8ff)
+
+
+#### Accuracy Graph
+
+![Accuracy Graph CNN](https://github.com/PiyushBL45t/DL-Simplified/assets/75735209/2c3d878e-bb68-4e7c-875d-f426ecf6d531)
+
+
+## <p align = "center">Results</p>
+
+<div align = "center">
+
+![CNN Result](https://github.com/PiyushBL45t/DL-Simplified/assets/75735209/4b2462bf-760a-48bb-960f-90dce1525307)
+
+</div>
+
+## Accuracy and training time comparison of all the Deep Learning Algorithms
+|             | Normal CNN | EfficientNet50 | InceptionV3 | MobileNetV2 |
+|-------------|------------|----------------|-------------|-------------|
+|Accuracy     | 97%        | 77%            | 86%         | 93%         |
+|Eval Metrics | None       | MAE            | MAE         | None        |
+|Train Time   | 15 mins    | 20 mins        | 20 mins     | 20 mins     |
+|Epochs       | 10         | 10             | 10          | 10          |
+
+
+## Techniques used for data preprocssing:
+1. Image Prepreocssing
+2. Data Preprocessing
+3. Image visualizations
+4. Setting up the path for defective and non defective images
+5. Data Labellling and annotations
+6. Building the CNN model
+7. Using the pretrained models and fine tuning them
+8. Converting the image data to numpy arrays
+9. Checking the loss and accuracy graphs for each DL algorithm used
+
+
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		# Pneumonia Detection using X-Ray images
		## Detaset link: https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia