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+# 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:**  
+  ```bash
+  curl -X POST -F "image=@motherboard.jpg" http://localhost:5000/detect
+  ```  
+- **Successful Response (200):**  
+  ```json
+  {
+    "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:**  
+```python
+import requests
+response = requests.post(
+    'http://localhost:5000/detect',
+    files={'image': open('motherboard.jpg', 'rb')}
+)
+```
+
+**Sample Response:**  
+```json
+{
+  "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    |