Ruang Tenun Machine Learning API

Ruang Tenun Machine Learning API is a tool for automatically detecting, analyzing, and classifying various types of woven fabrics using machine learning technology.

Development

Requirements

• Python 3.x
• Flask
• Other required dependencies (specified in the requirements.txt file)

Installation

1. Clone the repository:

   git clone https://github.com/ruang-tenun/Ruang-Tenun-ML-API.git
   cd Ruang-Tenun-ML-API

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

Running the Application

1. Set the FLASK_APP environment variable:

   export FLASK_APP=app.py  # On Windows use `set FLASK_APP=app.py`

2. Run the Flask application:

   flask run

The application will be available at http://127.0.0.1:5000/.

Endpoint

Tenun Detection

• URL: http://127.0.0.1:5000/predict
• Method: POST
• Description: This endpoint accepts an image of woven fabric and returns the classification result along with a confidence score.

Request

• Content-Type: multipart/form-data (for file uploads)

• Data Params:

  {
      "image": <file image>
  }

The image parameter should be a file (JPEG, PNG, etc.) representing the woven fabric you want to classify.

Response

• Content-Type: application/json

• Body:

  {
      "confidence_score": 0.996875524520874,
      "created_at": "2024-12-12T13:35:08.962219",
      "id": "e9b1c91d-6b48-452f-bd0e-62ceb7bb15eb",
      "result": "Endek Bali"
  }

Example Usage

Using curl

Send an image for prediction:

curl -X POST -F 'image=@path/to/your/image.jpg' http://127.0.0.1:5000/predict