Hand Gesture Detection
Detect and recognise hand gestures in any image. Identifies 35 classes digits 1–9 and letters A–Z perfect for sign language interfaces, gesture-controlled IoT, and HCI projects.
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Get API Key
Generate your API key from the dashboard
Upload Gesture Image
POST a photo of a hand showing a gesture
Get Recognition Results
Receive gesture class, confidence, and bounding box
cd_xxxxxxxxxxxxxxxxxxxxGesture Image
Upload Image
Upload an image for analysis. Use a clear, well-lit photo for best results.
Click or drag & drop
JPG, PNG up to 5MB
Minimum detection confidence lower values catch partially visible gestures but may increase false positives
Result
No result yet
Upload an image and run the test to see the annotated output
1#!/usr/bin/env python3
2"""
3Raspberry Pi - CircuitDigest Hand Gesture Detection API
4--------------------------------------------------------
5Captures a frame with Pi Camera / USB webcam, sends it to
6the cloud API, and prints the detected gestures.
7
8Install: pip install requests
9"""
10import requests
11
12API_URL = "https://www.circuitdigest.cloud/api/v1/hand-gesture-detection/detect"
13API_KEY = "YOUR_API_KEY"
14
15def detect_gesture(image_path: str) -> dict:
16 with open(image_path, "rb") as img:
17 response = requests.post(
18 API_URL,
19 headers={"X-API-Key": API_KEY},
20 files={"imageFile": img},
21 timeout=30,
22 )
23 response.raise_for_status()
24 return response.json()
25
26def main():
27 result = detect_gesture("gesture.jpg")
28
29 if result["status"] == "success":
30 print(f"Gestures detected: {result['gesture_count']}")
31 for g in result["detected_gestures"]:
32 print(f" {g['gesture']} ({g['confidence']:.1f}% confidence)")
33 else:
34 print(f"Status: {result['status']} - {result.get('message', '')}")
35
36if __name__ == "__main__":
37 main()Tutorials
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