Detection Smarter

This repository contains a Flask-based API for image detection and text recognition using OpenCV and Tesseract. The API provides endpoints for uploading images, detecting objects or text within images, and downloading processed images.

Table of Contents

• Detection Smarter
  • Table of Contents
  • Installation
  • Usage
  • API Endpoints
    • Home
    • Detect Image
    • List Scene Images
    • Download Image
    • Upload Scene Image
    • Detect Text Tree
    • Python Detect Image
  • File Structure
    • Explanation of Files
  • Migration to openai>=1.0.0
    • Example Usage
  • Contributing
  • License

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/detection_smarter.git
   cd detection_smarter

2. Create a virtual environment and activate it:

   python3 -m venv venv
   source venv/bin/activate

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Start the Flask server:

   python src/api/index.py

2. The server will run on port 4721 by default. You can access the API at http://localhost:4721.

API Endpoints

Home

• GET /

  Returns a simple message to confirm the server is running.

  curl http://localhost:4721/

Detect Image

• POST /detect/image

  Detect objects or text in an uploaded image.

  Parameters:

  • image: The image file to be uploaded.
  • scene_option: The scene option for detection.
  • detect_option: The detection option (icon or text).
  • contrast (optional): Contrast setting for text detection.
  • option_compare (optional): Option compare setting for text detection.
  • threshold (optional): Threshold setting for text detection.

  curl -F "image=@path/to/your/image.png" "http://localhost:4721/detect/image?scene_option=option&detect_option=icon"

List Scene Images

• GET /scene/list

  List all scene images.

  curl http://localhost:4721/scene/list

Download Image

• GET /download/<image_name>

  Download a processed image by name.

  curl http://localhost:4721/download/image_name.png

Upload Scene Image

• POST /scene/upload

  Upload a new scene image.

  Parameters:

  • image: The image file to be uploaded.
  • image_name: The name to save the image as.

  curl -F "image=@path/to/your/image.png" "http://localhost:4721/scene/upload?image_name=image_name"

Detect Text Tree

• POST /detect/text/tree

  Detect text in an uploaded image and return the text tree structure.

  Parameters:

  • image: The image file to be uploaded.
  • contrast (optional): Contrast setting for text detection.
  • threshold (optional): Threshold setting for text detection.

  curl -F "image=@path/to/your/image.png" "http://localhost:4721/detect/text/tree"

Python Detect Image

• POST /py/detect/image

  Detect objects in an uploaded image using a Python-based detection method.

  Parameters:

  • image: The image file to be uploaded.
  • nameTemplate: The template name for detection.

  curl -F "image=@path/to/your/image.png" "http://localhost:4721/py/detect/image?nameTemplate=template_name"

File Structure

detection_smarter/
├── src/
│   ├── api/
│   │   └── index.py          # Main Flask API server
│   ├── core/
│   │   ├── index.py          # Core detection logic
│   │   ├── scenes.py         # Scene image handling
│   │   └── tesseract.py      # Text detection logic
│   └── utils/
│       ├── result/           # Directory for processed images
│       └── image_scenes/     # Directory for scene images
├── requirements.txt          # Python dependencies
└── README.md                 # Project documentation

Explanation of Files

• src/api/index.py: This is the main entry point for the Flask API server. It defines the routes and handlers for the API endpoints.
• src/core/index.py: Contains the core logic for detecting objects or text within images.
• src/core/scenes.py: Handles operations related to scene images, such as uploading and listing scene images.
• src/core/tesseract.py: Implements text detection logic using Tesseract OCR.
• src/utils/result/: Directory where processed images are stored.
• src/utils/image_scenes/: Directory where scene images are stored.
• requirements.txt: Lists the Python dependencies required for the project.
• README.md: Project documentation, including installation instructions, usage, and API endpoint details.

Migration to openai>=1.0.0

This project has been updated to use the new openai API interface. The openai.Completion method has been replaced with openai.ChatCompletion.create.

Example Usage

import openai

def get_completion(prompt):
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": prompt}
        ]
    )
    return response.choices[0].message['content']

Make sure to update your requirements.txt to include openai>=1.0.0.

Contributing

Feel free to submit issues or pull requests if you have any improvements or bug fixes.

License

This project is licensed under the MIT License.