Memory Module Detection API Documentation

Overview

Flask API for detecting memory modules on motherboard images using YOLOv8. Processes uploaded images and returns bounding box coordinates with confidence scores.

Base URL

http://localhost:5000

Endpoints

1. Root Endpoint

GET /

Returns the test interface HTML page
Response: test.html

2. Image Detection

POST /detect

Accepts image uploads for processing

Request:

curl -X POST -F "image=@motherboard.jpg" http://localhost:5000/detect

Successful Response (200):

{
  "detections": [
    {
      "box": [x1,y1,x2,y2],
      "confidence": 0.95,
      "class": 0
    }
  ],
  "result_image": "/results/filename.jpg"
}

Error Responses:
- 400 Bad Request: Missing/invalid image file
- 500 Server Error: Processing failure

3. Result Retrieval

GET /results/<filename>

Returns annotated image with bounding boxes
Example: http://localhost:5000/results/out1.jpg

Request/Response Examples

Sample Request:

import requests
response = requests.post(
    'http://localhost:5000/detect',
    files={'image': open('motherboard.jpg', 'rb')}
)

Sample Response:

{
  "detections": [
    {
      "box": [541,567,661,265],
      "confidence": 0.98,
      "class": 0
    }
  ],
  "result_image": "/results/out1.jpg"
}

Technical Specifications

Parameter	Value
Model	YOLOv8n (custom-trained)
Input Formats	JPG/PNG
Recommended Resolution	416px
Processing Time (CPU)	200-500ms per image

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