gestures/gesture_recognition.py

@@ -1,61 +1,35 @@
 import cv2
 import mediapipe as mp
+import simple_gestures_lib as sgest
 
 mp_drawing = mp.solutions.drawing_utils
 mp_hands = mp.solutions.hands
 from math import sqrt
 
 
-def calculate_distance(ax, ay, bx, by):
-    distance = sqrt(((bx - ax) ** 2 + (by - ay) ** 2))
-    return distance
-
 
 hands = mp_hands.Hands(
     min_detection_confidence=0.5, min_tracking_confidence=0.5)
 cap = cv2.VideoCapture(0)
 while cap.isOpened():
     success, image = cap.read()
-
-    # Flip the image horizontally for a later selfie-view display, and convert
-    # the BGR image to RGB.
     image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
-    # To improve performance, optionally mark the image as not writeable to
-    # pass by reference.
     image.flags.writeable = False
     results = hands.process(image)
 
-    # Draw the hand annotations on the image.g
     image.flags.writeable = True
     image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
     if results.multi_hand_landmarks:
         for hand_landmarks in results.multi_hand_landmarks:
             mp_drawing.draw_landmarks(
                 image, hand_landmarks, mp_hands.HAND_CONNECTIONS)
-            # print(hand_landmarks)        ## spójrz na to
     if cv2.waitKey(33) == ord('s'):
         if results.multi_hand_landmarks:
-            i = 0
             for hand_landmarks in results.multi_hand_landmarks:
-                ax = hand_landmarks.landmark[8].x
-                ay = hand_landmarks.landmark[8].y
-                bx = hand_landmarks.landmark[5].x
-                by = hand_landmarks.landmark[5].y
-                distance_8_5 = calculate_distance(ax, ay, bx, by)
-                print(distance_8_5)
-                ax = hand_landmarks.landmark[5].x
-                ay = hand_landmarks.landmark[5].y
-                bx = hand_landmarks.landmark[0].x
-                by = hand_landmarks.landmark[0].y
-                distance_5_0 = calculate_distance(ax, ay, bx, by)
-                print(distance_5_0)
-                if (distance_5_0 < distance_8_5 + 0.1):
-                    print("wyprostowany")
-                else:
-                    print("niewyprostowany")
-
-                # i += 1
-                # print(hand_landmarks.)
+                print(sgest.check_index_finger(hand_landmarks))
+                print(sgest.check_middle_finger(hand_landmarks))
+                print(sgest.check_ring_finger(hand_landmarks))
+                print(sgest.check_pinky_finger(hand_landmarks))
 
     cv2.imshow('MediaPipe Hands', image)
     if cv2.waitKey(5) & 0xFF == 27:

gestures/simple_gestures_lib.py

@@ -0,0 +1,78 @@
+from math import sqrt
+
+def calculate_distance(ax, ay, bx, by):
+    distance = sqrt(((bx - ax) ** 2 + (by - ay) ** 2))
+    return distance
+
+def check_index_finger(hand_landmarks):
+    ax = hand_landmarks.landmark[8].x
+    ay = hand_landmarks.landmark[8].y
+    bx = hand_landmarks.landmark[5].x
+    by = hand_landmarks.landmark[5].y
+    distance_8_5 = calculate_distance(ax, ay, bx, by)
+    ax = hand_landmarks.landmark[5].x
+    ay = hand_landmarks.landmark[5].y
+    bx = hand_landmarks.landmark[0].x
+    by = hand_landmarks.landmark[0].y
+    distance_5_0 = calculate_distance(ax, ay, bx, by)
+
+    if (distance_5_0 < distance_8_5 + 0.1):
+        result = "wskazujacy_wyprostowany"
+    else:
+        result = "wskazujacy_niewyprostowany"
+    return (result, hand_landmarks.landmark[8].x, hand_landmarks.landmark[8].y)
+
+def check_middle_finger(hand_landmarks):
+    ax = hand_landmarks.landmark[12].x
+    ay = hand_landmarks.landmark[12].y
+    bx = hand_landmarks.landmark[9].x
+    by = hand_landmarks.landmark[9].y
+    distance_12_9 = calculate_distance(ax, ay, bx, by)
+    ax = hand_landmarks.landmark[9].x
+    ay = hand_landmarks.landmark[9].y
+    bx = hand_landmarks.landmark[0].x
+    by = hand_landmarks.landmark[0].y
+    distance_9_0 = calculate_distance(ax, ay, bx, by)
+
+    if (distance_9_0 < distance_12_9 + 0.1):
+        result = "srodkowy_wyprostowany"
+    else:
+        result = "srodkowy_niewyprostowany"
+    return (result, hand_landmarks.landmark[12].x, hand_landmarks.landmark[12].y)
+
+def check_ring_finger(hand_landmarks):
+    ax = hand_landmarks.landmark[16].x
+    ay = hand_landmarks.landmark[16].y
+    bx = hand_landmarks.landmark[13].x
+    by = hand_landmarks.landmark[13].y
+    distance_16_13 = calculate_distance(ax, ay, bx, by)
+    ax = hand_landmarks.landmark[13].x
+    ay = hand_landmarks.landmark[13].y
+    bx = hand_landmarks.landmark[0].x
+    by = hand_landmarks.landmark[0].y
+    distance_13_0 = calculate_distance(ax, ay, bx, by)
+
+    if (distance_13_0 < distance_16_13 + 0.1):
+        result = "serdeczny_wyprostowany"
+    else:
+        result = "serdeczny_niewyprostowany"
+    return (result, hand_landmarks.landmark[16].x, hand_landmarks.landmark[16].y)
+
+def check_pinky_finger(hand_landmarks):
+    ax = hand_landmarks.landmark[20].x
+    ay = hand_landmarks.landmark[20].y
+    bx = hand_landmarks.landmark[17].x
+    by = hand_landmarks.landmark[17].y
+    distance_20_17 = calculate_distance(ax, ay, bx, by)
+    ax = hand_landmarks.landmark[17].x
+    ay = hand_landmarks.landmark[17].y
+    bx = hand_landmarks.landmark[0].x
+    by = hand_landmarks.landmark[0].y
+    distance_17_0 = calculate_distance(ax, ay, bx, by)
+
+    if (distance_17_0 < distance_20_17 + 0.1):
+        result = "maly_wyprostowany"
+    else:
+        result = "maly_niewyprostowany"
+    return (result, hand_landmarks.landmark[20].x, hand_landmarks.landmark[20].y)
+