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21
LICENSE
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21
LICENSE
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MIT License
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Copyright (c) 2026 Bilal-Alasha
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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1233
main.ipynb
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1233
main.ipynb
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تم حذف اختلاف الملف لأن أحد الأسطر أو أكثر طويلة جداً
ثنائية
prediction_probabilities.npy
Normal file
ثنائية
prediction_probabilities.npy
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ملف ثنائي غير معروض.
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readme.md
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readme.md
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# Plant Leaf Disease Classification and confedence Estimation using Neural Networks with Fuzzy Logic
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The Model was trained and reported by Bilal Al Asha and the fuzzy logic code and report was done by mahdi alwis
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## Prerequisites
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- **Python** – Version **3.11.9** or later **3.12.10**
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- **pip** – Python package installer
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## Setup Instructions
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### 1. Download the Dataset
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Download the dataset from the following link:
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[`https://www.kaggle.com/datasets/emmarex/plantdisease`]
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### 2. Remove Existing Dataset Files
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> **Important:** Before proceeding, **delete any file with the same name as the dataset** inside the main dataset folder when you get it.
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> Failure to do so will cause the model to **memorize** the data during training, leading to incorrect results.
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### 3. Create and Activate a Virtual Environment
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Open a terminal in the project root directory and run:
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```bash
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python -m venv venv
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```
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Activate the environment:a
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OS Command
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Windows venv\Scripts\activate
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Linux source venv/bin/activate
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macOS source venv/bin/activate
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Install Dependencies
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```bash
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pip install -r requirements.txt
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```
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Configure Jupyter Kernel (if using Jupyter Notebook)
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f you plan to use Jupyter Notebook, make sure to select the newly created virtual environment as the kernel:
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Open Jupyter Notebook
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Go to Kernel → Change kernel
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Select the kernel named after your virtual environment (e.g., venv)
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ثنائية
requirements.txt
Normal file
ثنائية
requirements.txt
Normal file
ملف ثنائي غير معروض.
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