https://github.com/prathamesh-patil-5090/image_recognition
An image recognition project that leverages deep learning techniques to classify and analyze images. The model is built using Python and TensorFlow/Keras, with a focus on recognizing and categorizing objects from various image datasets.
https://github.com/prathamesh-patil-5090/image_recognition
django ocr ocr-python python
Last synced: 17 days ago
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An image recognition project that leverages deep learning techniques to classify and analyze images. The model is built using Python and TensorFlow/Keras, with a focus on recognizing and categorizing objects from various image datasets.
- Host: GitHub
- URL: https://github.com/prathamesh-patil-5090/image_recognition
- Owner: prathamesh-patil-5090
- Created: 2024-10-28T02:21:54.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-29T02:43:39.000Z (over 1 year ago)
- Last Synced: 2025-10-19T17:39:02.610Z (8 months ago)
- Topics: django, ocr, ocr-python, python
- Language: HTML
- Homepage:
- Size: 3 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Image Recognition
## Description
The Image Recognition project is an OCR-based image recognition system using Django and PyTesseract to convert images into readable text. This application provides easy methods to upload images, extract text, and view recognized data.
## Table of Contents
- [Technologies Used](#technologies-used)
- [Project Structure](#project-structure)
- [Setup Instructions](#setup-instructions)
- [Usage](#usage)
- [Contribution Guidelines](#contribution-guidelines)
- [License](#license)
## Technologies Used
- Python
- Django (Backend)
- PyTesseract (OCR Engine)
- HTML/CSS (Frontend)
## Usage
1. Upload Image: Use the upload page to submit images.
2. Extract Text: View recognized text on the result page.
## Project Structure
```plaintext
Image_Recognition/
├── ocr/
│ ├── views.py
│ ├── templates/
│ │ ├── upload.html
│ │ └── result.html
├── manage.py
├── db.sqlite3
└── requirements.txt
```
## Setup Instructions
1. Set Up Virtual Environment
```bash
python -m venv .venv
source .venv/bin/activate # For Windows: .venv\Scripts\activate
```
2. Install Dependencies
```bash
pip install -r requirements.txt
```
3. Database Migration
```bash
python manage.py migrate
```
4. Run the Server
```bash
python manage.py runserver
```
## Contribution Guidelines
1. Fork the repository.
2. Create a feature branch (git checkout -b feature/AmazingFeature).
3. Commit your changes (git commit -m 'Add some AmazingFeature').
4. Push to the branch (git push origin feature/AmazingFeature).
5. Open a pull request.
## License
This project is licensed under the MIT License.
## Screenshots:
