How m-saad-k/robotic-servo-hand-controlled-raspberry-pi-5-and-pi-camera-with-mediapipe works
This Raspberry Pi application captures camera frames, uses MediaPipe landmarks to determine finger positions, and maps those results to servo angles while displaying a live preview. The README also describes the Raspberry Pi camera and Python-environment setup, but that setup is not part of the runtime architecture. The graph reflects the sampled source; the imported speech library is unused, and no speech capability is documented.
Main entry points: Cam_Controlled_Servo_Hand.py Hand controller · module.py Landmark helpers
Components 8
Frame capture
- Hand controller
hand-tracker-code/Cam_Controlled_Servo_Hand.py - Pi camera
Hand analysis
- Landmark helpers
hand-tracker-code/module.py - MediaPipe Hands
- Finger detection
hand-tracker-code/Cam_Controlled_Servo_Hand.py
Output control
- Live preview
- Servo hand
Other components
- Operator
Connections 10
- Operator → Hand controller: starts
- Hand controller → Pi camera: captures frames
- Pi camera → Hand controller: returns frames
- Hand controller → Landmark helpers: requests landmarks
- Landmark helpers → MediaPipe Hands: processes frames
- MediaPipe Hands → Landmark helpers: returns landmarks
- Landmark helpers → Hand controller: returns positions and names
- Hand controller → Finger detection: checks finger positions
- Hand controller → Live preview: shows frames
- Hand controller → Servo hand: sets servo angles