Instructions to Run the Code

1. Clone the repo and Change Directory to image_processor

git clone https://github.com/FaizAlam/image_processor.git && cd image_processor

2. Create a Virtual Python Environment

python3 -m venv myvenv

3. Activate the Environment

• Windows:

  .\myvenv\Scripts\activate

• macOS/Linux:

  source myvenv/bin/activate

4. Install Dependencies

pip install -r requirements.txt

5. Run the migration command

python3 manage.py migrate

6. Run the Django Server

python3 manage.py runserver

7. Run the Celery Worker

celery -A image_processor worker -l info

Testing

• After starting the server, you can test the API using the Postman collection:
  • Postman API Collection

API Documentation

UPLOAD API

Endpoint: /upload/

Method: POST

Description: Upload a CSV file containing product information and image URLs. The system validates the CSV, stores the data, and asynchronously processes the images.

Request:

• Headers:
  • Content-Type: multipart/form-data
• Body:
  • file: The CSV file to be uploaded. It should contain columns Serial Number, Product Name, and Input Image Urls.

Response:

• Success (200 OK): Returns a unique request_id that can be used to track the status of the image processing.

  {
    "request_id": "123e4567-e89b-12d3-a456-426614174000"
  }

• Error:
  • File not provided
  • CSV validation failed
  • Internal server error

GET STATUS API

Endpoint: /status/<request_id>/

Method: GET

Description: Check the status of the image processing request using the request_id returned by the upload API.

Request:

• Headers:
  • Content-Type: application/json
• Parameters:
  • request_id: UUID of the processing request.

Response:

• Success (200 OK):

  {
    "request_id": "1ded0e1c-83a5-4a4f-bcd8-2871bc0b9299",
    "status": "Completed",
    "images_processed": 14,
    "images_total": 14
  }

  or

  {
    "request_id": "1ded0e1c-83a5-4a4f-bcd8-2871bc0b9299",
    "status": "Pending",
    "images_processed": 1,
    "images_total": 14
  }

• Error:

  • Wrong request_id