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recognize finger straight

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Michal Maciaszek 2020-12-29 21:46:50 +01:00
parent 1bbade4884
commit 8aec2319d1
1 changed files with 44 additions and 46 deletions
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90
gestures/gesture_recognition.py
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@ -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()