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ConvexHullFingerCountVideo.py
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ConvexHullFingerCountVideo.py
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import cv2
import numpy as np
def calcDistance(pt1, pt2):
x_diff = (pt1[0]-pt2[0])
y_diff = (pt1[1]-pt2[1])
return int(np.sqrt(x_diff**2+y_diff**2))
def getConvexHull(imgSrc, mask):
contours, hierarchy = cv2.findContours(
mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
if len(contours) != 0:
c = max(contours, key=cv2.contourArea)
hull = cv2.convexHull(c, returnPoints=False)
hull[::-1].sort(axis=0)
if cv2.contourArea(c)/(imgSrc.shape[0]*imgSrc.shape[1]) >= 0.14:
# print('The area is:', cv2.contourArea(
# c)/(imgSrc.shape[0]*imgSrc.shape[1]))
defects = cv2.convexityDefects(c, hull)
reducedHullPoints = gethullClusters(hull, c)
reducedDefects = getDefectClusters(c, defects)
hullAreaFraction = getHullArea(
reducedHullPoints)/(imgSrc.shape[0]*imgSrc.shape[1])
# print('the convex hull area is', hullAreaFraction)
drawHullPoints(imgSrc, reducedHullPoints)
drawDefects(imgSrc, c, reducedDefects)
if hullAreaFraction<=0.19 and hullAreaFraction>=0.17:
return 1
elif hullAreaFraction<=0.17:
return 0
else:
return len(reducedDefects)+1
def getHullArea(hullPtList):
pt_list = []
for pt in hullPtList:
pt_list.append(np.asarray([pt]))
pt_list = np.asarray(pt_list)
area = cv2.contourArea(pt_list)
return area
def getDefectClusters(contour, defects):
clusterPts = []
for defect in defects:
dis = defect[0][3]
ptA = contour[defect[0][0]][0]
ptB = contour[defect[0][1]][0]
defectPt = contour[defect[0][2]][0]
sideA = np.linalg.norm(ptB-defectPt)
sideB = np.linalg.norm(ptA-defectPt)
defectSide = np.linalg.norm(ptB-ptA)
# finding the angle
alpha = np.arccos((np.square(sideA) + np.square(sideB) -
np.square(defectSide))/(2*sideA*sideB))
# converting it into degrees
alpha = alpha*(180/np.pi)
# print(':',alpha)
if dis >= 3600 and alpha < 90.0:
clusterPts.append(defect)
# print()
return clusterPts
pass
def getRequiredDefects(defects):
defectClusters = getDefectClusters(defects)
pass
def gethullClusters(hull, contour):
listPoints = []
for pointIdx in hull:
listPoints.append(list(contour[pointIdx[0]][0]))
return getClusters(listPoints)
def drawHullPoints(imgSrc, pointsList):
for pt in pointsList:
# print('::',pt)
imgSrc = cv2.circle(imgSrc, (pt[0], pt[1]), 13, (255, 0, 255), 1)
def getClusters(pointSet, thres=30):
clusterPts = []
for pt in pointSet:
if clusterPts == []:
clusterPts.append((pt[0], pt[1]))
else:
inserted = False
for clusterCenter in clusterPts:
if calcDistance(clusterCenter, ((pt[0], pt[1]))) <= thres:
clusterCenter = (
(clusterCenter[0]+pt[0])//2, (clusterCenter[1]+pt[1])//2)
inserted = True
break
if not inserted:
clusterPts.append((pt[0], pt[1]))
return clusterPts
def drawDefects(imgSrc, contour, ptsList):
for i in range(len(ptsList)):
s, e, f, d = ptsList[i][0]
start = tuple(contour[s][0])
end = tuple(contour[e][0])
far = tuple(contour[f][0])
cv2.line(imgSrc, start, end, [0, 255, 0], 2)
cv2.circle(imgSrc, far, 5, [0, 0, 255], 2)
cv2.circle(imgSrc, start, 5, [255, 255, 255], 2)
cv2.circle(imgSrc, end, 5, [255, 255, 255], 2)
def drawConvexHull(imgSrc, hull):
cv2.drawContours(imgSrc, [hull], -1, (255, 0, 0), 2)
cap = cv2.VideoCapture('./vid/hand-gesture.mp4')
if not cap:
print('Camera cant be opened')
exit()
font = cv2.FONT_HERSHEY_SIMPLEX
thickness =2
fontScale = 1
color = (0,0,0)
while True:
ret, frame = cap.read()
if not ret:
# print('Frame read incorrectly')
break
frame = cv2.blur(frame, (3,3))
frame_HLS = cv2.cvtColor(frame, cv2.COLOR_BGR2HLS)
mask = cv2.inRange(frame_HLS, (0, 25, 13), (15, 204, 153))
try:
detection = getConvexHull(frame, mask)
finally:
if detection !=None:
frame = cv2.putText(frame, str(detection), (50,50), font,
fontScale, color, thickness, cv2.LINE_AA)
# print('===================================>Detected:', detection)
cv2.imshow('mask', mask)
cv2.imshow('img', frame)
pressedKey = cv2.waitKey(30) &0xFF
if pressedKey == ord('q'):
break
cap.release()
cv2.destroyAllWindows()