{"id":17695588,"url":"https://github.com/knightkun77/image_classification_project","last_synced_at":"2026-01-24T00:52:24.205Z","repository":{"id":258909070,"uuid":"872989405","full_name":"KnightKun77/image_classification_project","owner":"KnightKun77","description":"Image Classification Using Python","archived":false,"fork":false,"pushed_at":"2024-10-15T12:52:27.000Z","size":12,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-23T04:14:56.012Z","etag":null,"topics":["keras","machine-learning","matplotlib","numpy","opencv","python","tensorflow","tikinter"],"latest_commit_sha":null,"homepage":"https://github.com/KnightKun77/image_classification_project","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/KnightKun77.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-15T12:22:42.000Z","updated_at":"2024-10-15T12:56:14.000Z","dependencies_parsed_at":"2024-10-22T06:02:22.220Z","dependency_job_id":null,"html_url":"https://github.com/KnightKun77/image_classification_project","commit_stats":null,"previous_names":["knightkun77/image_classification_project"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KnightKun77%2Fimage_classification_project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KnightKun77%2Fimage_classification_project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KnightKun77%2Fimage_classification_project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KnightKun77%2Fimage_classification_project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/KnightKun77","download_url":"https://codeload.github.com/KnightKun77/image_classification_project/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250366716,"owners_count":21418772,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["keras","machine-learning","matplotlib","numpy","opencv","python","tensorflow","tikinter"],"created_at":"2024-10-24T14:06:08.155Z","updated_at":"2026-01-24T00:52:24.174Z","avatar_url":"https://github.com/KnightKun77.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Image Classification Using Python\n\n## Overview\n\nThis project is an image classification application that utilizes the CIFAR-10 dataset. It enables users to upload images and classify them using a trained deep learning model. The application features a user-friendly graphical interface that allows for easy interaction and visualization of classification results.\n\n## Table of Contents\n\n- [Features](#features)\n- [Technologies Used](#technologies-used)\n- [Setup Instructions](#setup-instructions)\n- [Usage](#usage)\n- [Dataset](#dataset)\n- [Model Training](#model-training)\n- [Dependencies](#dependencies)\n- [License](#license)\n- [Contributing](#contributing)\n\n## Features\n\n- User-friendly GUI for easy image upload and classification.\n- Image classification using a pre-trained model on the CIFAR-10 dataset.\n- Displays predicted class and confidence scores for classified images.\n- Option to upload multiple images for classification.\n\n## Technologies Used\n\n- **Python 3.x**\n- **TensorFlow**: For model training and inference.\n- **Keras**: For building and training the neural network.\n- **NumPy**: For numerical operations.\n- **OpenCV**: For image processing.\n- **Tkinter**: For creating the graphical user interface (GUI).\n- **Matplotlib**: For visualizing results (if applicable).\n\n## Setup Instructions\n\nFollow these steps to set up the project on your local machine:\n\n1. **Clone the Repository:**\n   Open your terminal or command prompt and run the following command:\n\n   ```bash\n   git clone https://github.com/KnightKun77/image_classification_project.git\n\n2. **Navigate to the Project Directory: Change your working directory to the cloned project folder:**\n    cd image_classification_project\n\n3. **Create a Virtual Environment (Optional but Recommended):**\n    python -m venv venv\n   **Activate the virtual environment:**\n    On Windows: venv\\Scripts\\activate\n    On macOS/Linux: source venv/bin/activate\n\n4. **Install Dependencies:**\n   Install the required packages using pip. If you have a requirements.txt file, you can install dependencies with: \n   pip install -r requirements.txt\n   If you don't have a requirements.txt file, you can manually install the necessary packages:\n   pip install tensorflow keras numpy opencv-python matplotlib\n\n## Usage\n\n1. **Run the Application:** After setting up the environment and installing the dependencies, run the application with:\n    bash\n    python main.py\n\n2. **Upload an Image:** Use the user interface to upload an image you want to classify. The application will process the image and display the predicted class \n    along with the confidence score.\n\n3. **View Results:** The classification result will be displayed on the screen. You can upload another image to classify more images.\n\n## Dataset\n\nThe CIFAR-10 dataset consists of 60,000 32x32 color images in 10 different classes, with 6,000 images per class. The classes are as follows:\n\nAirplane\nAutomobile\nBird\nCat\nDeer\nDog\nFrog\nHorse\nShip\nTruck\nThe dataset is divided into 50,000 training images and 10,000 test images.\n\n## Model Training\n\nTo train the model, ensure you have the CIFAR-10 dataset available. The training script (if provided) will load the dataset, preprocess the images, and build a convolutional neural network (CNN) to classify the images. Once trained, the model will be saved for use in the application.\n\nTraining Steps\nLoad the CIFAR-10 dataset.\nPreprocess the images (normalization, resizing, etc.).\nBuild and compile the CNN model.\nTrain the model on the training dataset.\nEvaluate the model on the test dataset.\nSave the trained model for inference.\n\n## Dependencies \nMake sure you have the following dependencies installed:\n\nPython: Ensure you have Python 3.x installed.\nTensorFlow: For model training and inference.\nKeras: For building and training the neural network.\nNumPy: For numerical operations.\nOpenCV: For image processing.\nTkinter: For creating the GUI.\nMatplotlib: For plotting (if applicable).\n\n## Contributing\n\nContributions are welcome! If you have suggestions for improvements or want to add features, please fork the repository and submit a pull request.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fknightkun77%2Fimage_classification_project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fknightkun77%2Fimage_classification_project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fknightkun77%2Fimage_classification_project/lists"}