detector = buildDetector()
# Define the codec and create VideoWriter object
out = cv2.VideoWriter('results.avi', -1, 15.0, (568, 640), True)
while (True):
i += 1
file_path = "frames_" + "%04d" % i + ".png"
print file_path
frame = cv2.imread(file_path, 1)
if frame == None:
break
#Find keypoints
keypoints, _ = findHolds(frame, detector)
#colors = findColors(frame,keypoints)
frameWithKeypoints = cv2.drawKeypoints(frame, keypoints, -1, [0, 0, 255])
results = np.concatenate((frame, frameWithKeypoints), axis=0)
print results.shape
out.write(results)
cv2.imshow('frame', results)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
#cap.release()
"""Example""" import holdDetector as hd #Open dialog to select image img = hd.openImage() # Set initial detector parameters hd.buildDetector(minArea = 500) # Finds each hold. Returns keypoints for each hold # and the points that define the contours of each hold holds, contours = hd.findHolds(img) #Finds a color associated with each keypoint colors = hd.findColors(img,holds) #Draws keypoints onto image and plots colors in 3D space hd.draw(img,holds) hd.plotColors(colors)
shape = (x,y)
# Open VideoWriter object
#codec = cv2.cv.CV_FOURCC('Y','V','1','2')
out = cv2.VideoWriter(path[:-4] + '-out.avi',-1, 30.0, shape,True)
while(cap.isOpened()):
# Capture frame-by-frame
ret, frame = cap.read()
if not ret:
break
# Find keypoints
keypoints, hulls = findHolds(frame)
frameWithKeypoints = cv2.drawKeypoints(frame,keypoints,-1,[0,0,255])
#cv2.drawContours(frame,hulls,-1,[255,0,0])
results = np.concatenate((frame, frameWithKeypoints), axis=axis)
# Write image to video out
out.write(results)
cv2.imshow('frame',results)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap = cv2.VideoCapture(0)
# Define the codec and create VideoWriter object
out = cv2.VideoWriter("webcam\\"+relpath,-1, 15.0, (640*2, 960/2),True)
detector = buildDetector()
while (cap.isOpened()):
start = time.time()
# Pull in frame from webcam
retval, frame = cap.read()
if retval == False:
break
#Find keypoints
keypoints, _ = findHolds(frame,detector)
#Draw Keypoints onto frame
frameWithKeypoints = cv2.drawKeypoints(frame,keypoints,-1,[0,0,255])
#Display frame with keypoint frame side by side.
results = np.concatenate((frame, frameWithKeypoints), axis=1)
# Write image to video out
out.write(results)
#Display for user.
cv2.imshow('frame',results)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
while(cap.isOpened()):
mask2 = np.zeros((c,r))
mask3 = np.zeros((c,r))
# Capture frame-by-frame
ret, frame = cap.read()
if not ret:
break
#Find keypoints
keypoints, _ = findHolds(frame)
for key in keypoints:
#mask[key.pt] =+25
cv2.circle(mask2,(int(key.pt[1]),int(key.pt[0])),5,2,-1)
mask +=
mask[mask > 0] = mask[mask > 0] - 1
mask3 = mask2 > 200
"""
for r,row in enumerate(mask):
for c,col in enumerate(row):
if mask[r,c] > 1:
cv2.circle(frame,(r,c),10,[0,0,255],-1)