Merge pull request #717 from Arihant-Bhandari/almond

[Project Addition] Turkey Almond Species Classification using DL
abhisheks008 · Jun 3, 2024 · 2478152 · 2478152
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diff --git a/Turkey Almond Species Classification using DL/Dataset/README.md b/Turkey Almond Species Classification using DL/Dataset/README.md
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+The link for the dataset used in this project:  https://www.kaggle.com/datasets/mahyeks/almond-varieties
+
+The dataset consists of 4 subdirectories under the main Dataset directory: AK(401 images), KAPADOKYA(465 images), NURLU(306 images) and SIRA(384 images). 
diff --git a/Turkey Almond Species Classification using DL/Images/ALMOND.png b/Turkey Almond Species Classification using DL/Images/ALMOND.png
diff --git a/Turkey Almond Species Classification using DL/Images/CNN Accuracy.png b/Turkey Almond Species Classification using DL/Images/CNN Accuracy.png
diff --git a/Turkey Almond Species Classification using DL/Images/CNN Loss.png b/Turkey Almond Species Classification using DL/Images/CNN Loss.png
diff --git a/Turkey Almond Species Classification using DL/Images/DENSENET121 Accuracy.png b/Turkey Almond Species Classification using DL/Images/DENSENET121 Accuracy.png
diff --git a/Turkey Almond Species Classification using DL/Images/DENSENET121 Loss.png b/Turkey Almond Species Classification using DL/Images/DENSENET121 Loss.png
diff --git a/Turkey Almond Species Classification using DL/Images/EDA.png b/Turkey Almond Species Classification using DL/Images/EDA.png
diff --git a/Turkey Almond Species Classification using DL/Images/EfficientNetB7 Accuracy.png b/Turkey Almond Species Classification using DL/Images/EfficientNetB7 Accuracy.png
diff --git a/Turkey Almond Species Classification using DL/Images/EfficientNetB7 Loss.png b/Turkey Almond Species Classification using DL/Images/EfficientNetB7 Loss.png
diff --git a/Turkey Almond Species Classification using DL/Images/InceptionV3 Accuracy.png b/Turkey Almond Species Classification using DL/Images/InceptionV3 Accuracy.png
diff --git a/Turkey Almond Species Classification using DL/Images/InceptionV3 Loss.png b/Turkey Almond Species Classification using DL/Images/InceptionV3 Loss.png
diff --git a/Turkey Almond Species Classification using DL/Images/RESNET50 Accuracy.png b/Turkey Almond Species Classification using DL/Images/RESNET50 Accuracy.png
diff --git a/Turkey Almond Species Classification using DL/Images/RESNET50 Loss.png b/Turkey Almond Species Classification using DL/Images/RESNET50 Loss.png
diff --git a/Turkey Almond Species Classification using DL/Images/VGG16 Accuracy.png b/Turkey Almond Species Classification using DL/Images/VGG16 Accuracy.png
diff --git a/Turkey Almond Species Classification using DL/Images/VGG16 Loss.png b/Turkey Almond Species Classification using DL/Images/VGG16 Loss.png
diff --git a/Turkey Almond Species Classification using DL/Images/Xception Accuracy.png b/Turkey Almond Species Classification using DL/Images/Xception Accuracy.png
diff --git a/Turkey Almond Species Classification using DL/Images/Xception Loss.png b/Turkey Almond Species Classification using DL/Images/Xception Loss.png
diff --git a/Turkey Almond Species Classification using DL/Model/almond-classify.ipynb b/Turkey Almond Species Classification using DL/Model/almond-classify.ipynb
diff --git a/Turkey Almond Species Classification using DL/README.md b/Turkey Almond Species Classification using DL/README.md
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+## **Turkey Almond Species Classification using DL**
+
+### 🎯 **Goal**
+
+The objective of this project is to classify images of almonds from various regions into four distinct varieties of Turkic almond species.
+
+### 🧵 **Dataset**
+
+The dataset consists of 4 subdirectories under the main Dataset directory: AK(401 images), KAPADOKYA(465 images), NURLU(306 images) and SIRA(384 images). The Dataset hence can be summarized as: 1556 images of the four varieties.
+
+### 🧾 **Description**
+
+The project deals with multi-class classification, classifying images into 4 classes of Turkey's indigenous almond species.
+
+### 🧮 **What I had done!**
+
+To achieve our goals, the following steps were implemented:
+
+- Images were loaded using keras.utils and normalized to the range 0 to 1.
+
+- Images were resized to a fixed size of 224x224 pixels.
+
+- Labels were converted from numerical to probability distribution representations.
+
+- Custom and pre-trained models were used for this task.
+
+### 🚀 **Models Implemented**
+
+models used:
+
+- ResNet-50
+- Xception
+- VGG16
+- CNN-Keras
+- InceptionV3
+- DenseNet-121
+- EfficientNetB7
+
+### 📚 **Libraries Needed**
+
+- Keras
+
+- Tensorflow
+
+- Numpy
+
+- Matplotlib
+
+### 📊 **Exploratory Data Analysis Results**
+
+
+- #### **Exploratory Data Analysis**
+
+<img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/ALMOND.png">
+
+<img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/EDA.png">
+
+- #### **CNN**
+
+<p align="center">
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/CNN%20Accuracy.png" height="400px" width="400px" />
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/CNN%20Loss.png" height="400px" width="400px" />
+</p>
+
+- #### **InceptionV3**
+
+<p align="center">
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/InceptionV3%20Accuracy.png" height="400px" width="400px" />
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/InceptionV3%20Loss.png" height="400px" width="400px" />
+</p>
+
+- #### **VGG16**
+
+<p align="center">
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/VGG16%20Accuracy.png" height="400px" width="400px" />
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/VGG16%20Loss.png" height="400px" width="400px" />
+</p>
+
+- #### **EfficientNetB7**
+
+<p align="center">
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/EfficientNetB7%20Accuracy.png" height="400px" width="400px" />
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/EfficientNetB7%20Loss.png" height="400px" width="400px" />
+</p>
+
+- #### **RESNET50**
+
+<p align="center">
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/RESNET50%20Accuracy.png" height="400px" width="400px" />
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/RESNET50%20Loss.png" height="400px" width="400px" />
+</p>
+
+- #### **DenseNet-121**
+
+<p align="center">
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/DENSENET121%20Accuracy.png" height="400px" width="400px" />
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/DENSENET121%20Loss.png" height="400px" width="400px" />
+</p>
+
+- #### **Xception**
+
+<p align="center">
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/Xception%20Accuracy.png" height="400px" width="400px" />
+  <img src="https://github.com/Arihant-Bhandari/DL-Simplified/blob/almond/Turkey%20Almond%20Species%20Classification%20using%20DL/Images/Xception%20Loss.png" height="400px" width="400px" />
+</p>
+
+### 📈 **Performance of the Models based on the Accuracy Scores**
+
+#### Metrics: 
+
+We used Validation and Testing **Loss** and **Accuracy** as metrics.
+
+| Models | Accuracy | Loss |
+|--------|---------------------|--------------------------|
+| ResNet-50 | 29.81% | 11.3137 |
+| InceptionV3 | 96.47%  | 0.1521 | 
+| CNN | 95.51% | 0.1550 |
+| VGG16 | 97.76% | 0.0680 |
+| EfficientNetB7 | 29.81% | 1.3967 |
+| DenseNet-121 | 98.72% | 0.0624 |
+| Xception | 97.44% | 0.0794 |
+
+### 📢 **Conclusion**
+
+We conclude the following:
+
+**DenseNet-121**, **Xception**, **VGG16**, **InceptionV3** and **CNN** work exceptionally well, with **DenseNet-121** being the clear winner.
+
+### ✒️ **Your Signature**
+
+Original Contributor: Arihant Bhandari [https://github.com/Arihant-Bhandari]
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		The link for the dataset used in this project: https://www.kaggle.com/datasets/mahyeks/almond-varieties

		The dataset consists of 4 subdirectories under the main Dataset directory: AK(401 images), KAPADOKYA(465 images), NURLU(306 images) and SIRA(384 images).