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img_test.py
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#carscade로 손검출
#손 위치 검출
#손 영역의 hsv값
#제스처 인식
import cv2
import numpy as np
import math
# 관심영역에서 z누르면 rgb를 hsv값으로 바꿔줌
def find_hsv_range(frame):
rows, cols = frame.shape
center_frame = frame[rows/2,cols/2]
hsv = cv2.cvtColor(center_frame,cv2.COLOR_BGR2HSV)
print(hsv)
return hsv
cap = cv2.VideoCapture(0)
while (1):
try: # an error comes if it does not find anything in window as it cannot find contour of max area
# therefore this try error statement
ret, frame = cap.read()
frame = cv2.flip(frame, 1)
kernel = np.ones((3, 3), np.uint8)
# define region of interest
roi = frame[100:300, 100:300]
#make_frame = roi를 짤라 (x :80~120, y: 90~130)범위를 짜름
make_frame = roi[90:130,80:120]
#hhhsv = make_frame을 hsv화 시킴
hhhsv = cv2.cvtColor(make_frame,cv2.COLOR_BGR2HSV)
rows, cols = hhhsv.shape[:2]
######### hhhsv[0][0] ~ hhhsv[40][40]의 평균 hsv를 구해보자#############
######문제 : hsv값 잡기가 힘들다
print(hhhsv[20][20])
cv2.imshow('hsv',hhhsv)
h= hhhsv[20][20][0]
s= hhhsv[20][20][1]
v= hhhsv[20][20][2]
cv2.rectangle(frame, (100, 100), (300, 300), (0, 255, 0), 0)
hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
# define range of skin color in HSV
# lower_skin = np.array([54, 131, 110], dtype=np.uint8)
# upper_skin = np.array([163, 157, 135], dtype=np.uint8)
# lower_skin = np.array([0, 133, 77], dtype=np.uint8)
#upper_skin = np.array([255, 173, 127], dtype=np.uint8)
if v>220:
max_v = 225
else:
max_v = v
if h<20:
h=20
max_h = h+20
min_h = 0
if h>100:
max_h = 180
min_h = max_h-30
if s<50:
s=50
lower_skin = np.array([min_h, s-30, v-50], dtype=np.uint8)
upper_skin = np.array([max_h, s+30, max_v+30], dtype=np.uint8)
# extract skin colur imagw
mask = cv2.inRange(hsv, lower_skin, upper_skin)
# extrapolate the hand to fill dark spots within
#mask = cv2.dilate(mask, kernel, iterations=4)
mask = cv2.erode(mask, kernel, iterations=1)
mask = cv2.dilate(mask, kernel, iterations=6)
# blur the image
mask = cv2.GaussianBlur(mask, (5, 5), 0)
# find contours
contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# find contour of max area(hand)
areas = [cv2.contourArea(c) for c in contours]
max_index = np.argmax(areas)
cnt = contours[max_index]
cv2.drawContours(mask,cnt,-1,(255,0,0),5)
#cnt = max(contours, key=lambda x: cv2.contourArea(x))
# approx the contour a little
epsilon = 0.0005 * cv2.arcLength(cnt, True)
approx = cv2.approxPolyDP(cnt, epsilon, True)
# make convex hull around hand
hull = cv2.convexHull(cnt)
# define area of hull and area of hand
areahull = cv2.contourArea(hull)
areacnt = cv2.contourArea(cnt)
# find the percentage of area not covered by hand in convex hull
arearatio = ((areahull - areacnt) / areacnt) * 100
# find the defects in convex hull with respect to hand
hull = cv2.convexHull(approx, returnPoints=False)
defects = cv2.convexityDefects(approx, hull)
# l = no. of defects
l = 0
# code for finding no. of defects due to fingers
for i in range(defects.shape[0]):
s, e, f, d = defects[i, 0]
start = tuple(approx[s][0])
end = tuple(approx[e][0])
far = tuple(approx[f][0])
pt = (100, 180)
# find length of all sides of triangle
a = math.sqrt((end[0] - start[0]) ** 2 + (end[1] - start[1]) ** 2)
b = math.sqrt((far[0] - start[0]) ** 2 + (far[1] - start[1]) ** 2)
c = math.sqrt((end[0] - far[0]) ** 2 + (end[1] - far[1]) ** 2)
s = (a + b + c) / 2
ar = math.sqrt(s * (s - a) * (s - b) * (s - c))
# distance between point and convex hull
d = (2 * ar) / a
# apply cosine rule here
angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c)) * 57
# ignore angles > 90 and ignore points very close to convex hull(they generally come due to noise)
if angle <= 90 and d > 30:
l += 1
cv2.circle(roi, far, 3, [255, 0, 0], -1)
# draw lines around hand
cv2.line(roi, start, end, [0, 255, 0], 2)
l += 1
# print corresponding gestures which are in their ranges
font = cv2.FONT_HERSHEY_SIMPLEX
if l == 1:
if areacnt < 2000:
cv2.putText(frame, 'Put hand in the box', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
else:
if arearatio < 12:
cv2.putText(frame, '0', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
elif arearatio < 17.5:
cv2.putText(frame, 'THUMBS UP', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
else:
cv2.putText(frame, '1(THUMBS UP)', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
elif l == 2:
cv2.putText(frame, '2', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
elif l == 3:
if arearatio < 27:
cv2.putText(frame, '3', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
else:
cv2.putText(frame, 'ok', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
elif l == 4:
cv2.putText(frame, '4', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
elif l == 5:
cv2.putText(frame, '5', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
elif l == 6:
cv2.putText(frame, 'reposition', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
else:
cv2.putText(frame, 'reposition', (10, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
# show the windows
cv2.imshow('mask', mask)
cv2.imshow('frame', frame)
except:
pass
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
cv2.destroyAllWindows()
cap.release()