This repository contains the Jupyter Notebook image_classifier.ipynb, which demonstrates the implementation of an image classification model using TensorFlow and OpenCV.
The notebook covers the following steps:
- Installation of Dependencies: Installing required libraries such as TensorFlow, OpenCV, and Matplotlib.
- Data Preprocessing: Loading and preprocessing images for training the model.
- Model Training: Training a convolutional neural network (CNN) for image classification.
- Model Evaluation: Evaluating the performance of the trained model.
- Results Visualization: Visualizing the classification results.
To run the notebook, ensure you have Python and Jupyter installed. Install the required libraries using the following command:
pip install -r requirements.txt-
Clone the repository:
git clone https://github.com/Harsh-Mathur-1503/opensourcelab.git cd opensourcelab -
Launch Jupyter Notebook:
jupyter notebook
-
Open
image_classifier.ipynband run the cells to execute the code.
The notebook includes sections that train the model and visualize the classification results, providing insights into the model's accuracy and performance.
If you would like to contribute to this project, please fork the repository and create a pull request with your changes.
This project is licensed under the MIT License. See the LICENSE file for more details.
For any questions or inquiries, please contact Harsh Mathur at harshmathur1503@gmail.com.