From 366145de0db915f6f754f8f1f4d67de93fb6154b Mon Sep 17 00:00:00 2001
From: Jimmy Allen <me@jimmy.nz>
Date: Tue, 2 Jan 2024 17:10:32 +1300
Subject: [PATCH] Add mediapipe hands example

---
 hands.py | 59 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 59 insertions(+)

diff --git a/hands.py b/hands.py
index e69de29..ee38dbc 100644
--- a/hands.py
+++ b/hands.py
@@ -0,0 +1,59 @@
+#!/usr/bin/python3
+
+import cv2
+
+from picamera2 import Picamera2
+import mediapipe as mp
+
+mp_drawing = mp.solutions.drawing_utils
+mp_drawing_styles = mp.solutions.drawing_styles
+mp_hands = mp.solutions.hands
+
+
+# Grab images as numpy arrays and leave everything else to OpenCV.
+
+cv2.startWindowThread()
+
+picam2 = Picamera2()
+picam2.configure(picam2.create_preview_configuration(main={"format": 'XRGB8888', "size": (1280, 720)}))
+picam2.start()
+
+cv2.namedWindow("Camera", cv2.WND_PROP_FULLSCREEN)
+cv2.setWindowProperty("Camera", cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
+
+with mp_hands.Hands(
+    model_complexity=0,
+    min_detection_confidence=0.5,
+    min_tracking_confidence=0.5,
+    max_num_hands=20) as hands:
+
+  while True:
+      image = picam2.capture_array()
+
+
+      image.flags.writeable = False
+      image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+      results = hands.process(image)
+
+      # Draw the hand annotations on the image.
+      image.flags.writeable = True
+      image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+
+    
+ 
+      if results.multi_hand_landmarks:
+        for hand_landmarks in results.multi_hand_landmarks:
+          x = hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP].x
+          y = hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP].y
+
+          mp_drawing.draw_landmarks(
+              image,
+              hand_landmarks,
+              mp_hands.HAND_CONNECTIONS,
+              mp_drawing_styles.get_default_hand_landmarks_style(),
+              mp_drawing_styles.get_default_hand_connections_style())
+      # Flip the image horizontally for a selfie-view display.
+      cv2.imshow("Camera", image)
+      if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+