From 8aec2319d10c2df04b390aabfaf1a8d758cad6e5 Mon Sep 17 00:00:00 2001
From: Michal Maciaszek <maciaszekm@wp.pl>
Date: Tue, 29 Dec 2020 21:46:50 +0100
Subject: [PATCH] recognize finger straight

---
 gestures/gesture_recognition.py | 90 ++++++++++++++++-----------------
 1 file changed, 44 insertions(+), 46 deletions(-)

diff --git a/gestures/gesture_recognition.py b/gestures/gesture_recognition.py
index 8ad8ff5..01a8030 100644
--- a/gestures/gesture_recognition.py
+++ b/gestures/gesture_recognition.py
@@ -1,66 +1,64 @@
 import cv2
 import mediapipe as mp
+
 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
 
+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()
+    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)
+    # 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'):
+    # Draw the hand annotations on the image.g
+    image.flags.writeable = True
+    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
     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
-        odleglosc_8_5 = calculate_distance(ax,ay, bx, by)
-        print(odleglosc_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
-        odleglosc_5_0 = calculate_distance(ax, ay, bx, by)
-        print(odleglosc_5_0)
-        if(odleglosc_5_0 < odleglosc_8_5 + 0.1):
-          print("wyprostowany")
-        else:
-          print("niewyprostowany")
+        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.)
 
-        # i += 1
-        # print(hand_landmarks.)
-
-  cv2.imshow('MediaPipe Hands', image)
-  if cv2.waitKey(5) & 0xFF == 27:
-    break
+    cv2.imshow('MediaPipe Hands', image)
+    if cv2.waitKey(5) & 0xFF == 27:
+        break
 hands.close()
 cap.release()
-