def createTrainingData(filename,time_start,time_stop):
vidcap = cv2.VideoCapture(filename)
try:
os.makedirs("trainingdata_"+filename)
except OSError:
pass
os.chdir("trainingdata_"+filename)
length = int(vidcap.get(cv2.CAP_PROP_FRAME_COUNT))
fps = int(vidcap.get(cv2.CAP_PROP_FPS))
for time in range(time_start,time_stop):
vidcap.set(cv2.CAP_PROP_POS_MSEC,time*1000)
success,image = vidcap.read()
image = cv2.medianBlur(image,7)
resized = imutils.resize(image, width=800)
p1 = resized[370:430,220:300]
p2 = resized[370:430,520:600]
p1 = cv2.Canny(p1, 400, 100, 255)
p2 = cv2.Canny(p2, 400, 100, 255)
cv2.imwrite('p1_'+str(time)+".png",p1)
cv2.imwrite('p2_'+str(time)+".png",p2)
os.chdir("..")
python类CAP_PROP_POS_MSEC的实例源码
def frame_iterator(filename, every_ms=1000, max_num_frames=300):
"""Uses OpenCV to iterate over all frames of filename at a given frequency.
Args:
filename: Path to video file (e.g. mp4)
every_ms: The duration (in milliseconds) to skip between frames.
max_num_frames: Maximum number of frames to process, taken from the
beginning of the video.
Yields:
RGB frame with shape (image height, image width, channels)
"""
video_capture = cv2.VideoCapture()
if not video_capture.open(filename):
print >> sys.stderr, 'Error: Cannot open video file ' + filename
return
last_ts = -99999 # The timestamp of last retrieved frame.
num_retrieved = 0
while num_retrieved < max_num_frames:
# Skip frames
while video_capture.get(CAP_PROP_POS_MSEC) < every_ms + last_ts:
if not video_capture.read()[0]:
return
last_ts = video_capture.get(CAP_PROP_POS_MSEC)
has_frames, frame = video_capture.read()
if not has_frames:
break
yield frame
num_retrieved += 1
def jump(self, frame=None, ms=None):
assert frame is not ms, "Use either frame or ms, not both!"
if frame:
if frame >= self.frames:
raise ReadFrameException('Cannot jump to frame (frame does not exists)')
self.vid.set(cv2.CAP_PROP_POS_FRAMES, frame)
if ms:
self.vid.set(cv2.CAP_PROP_POS_MSEC, ms)
# print("jumped to frame %i" % self.vid.get(cv2.CAP_PROP_POS_FRAMES))
def video2image():
cap = cv2.VideoCapture(args.videopath)
i = 0
name = 0
while cap.isOpened():
ret, frame = cap.read()
time = cap.get(cv2.CAP_PROP_POS_MSEC)
index = cap.get(cv2.CAP_PROP_POS_FRAMES)
print('frames: %d --- times: %f' % (index, time/1000))
if frame is None:
break
i += 1
if args.videofps <= 0:
cv2.imwrite(os.path.join(args.imagepath, str(name)) + '.jpg', frame)
name += 1
print('(height: %d, weight: %d, channel: %d)' % frame.shape)
else:
if i == args.videofps:
# cv2.imshow('frame', frame)
# k = cv2.waitKey(20)
# k = cv2.waitKey(0)
i = 0
cv2.imwrite(os.path.join(args.imagepath, str(name)) + '.jpg', frame)
name += 1
print('(height: %d, weight: %d, channel: %d)' % frame.shape)
cap.release()
cv2.destroyAllWindows()
def update_termites(self):
"""Update termites positions.
Args:
None.
Returns:
None.
"""
for termite in self.termites:
found, termite.position = termite.tracker.update(self.video_source.current_frame)
if not found:
print('Lost termite no.{}'.format(termite.identity))
self.video_source.pause()
termite.path.append([int(termite.position[0]), int(termite.position[1]),
self.video_source.source.get(cv2.CAP_PROP_POS_MSEC)])
def videoToImageArray(filename,time_start,time_stop):
vidcap = cv2.VideoCapture(filename)
pictures = [[],[]]
for time in range(time_start,time_stop):
vidcap.set(cv2.CAP_PROP_POS_MSEC,time*1000) # just cue to 20 sec. position
success,image = vidcap.read()
image = cv2.medianBlur(image,7)
resized = imutils.resize(image, width=800)
p1 = resized[370:430,220:300]
p2 = resized[370:430,520:600]
p1 = cv2.Canny(p1, 400, 100, 255)
p2 = cv2.Canny(p2, 400, 100, 255)
pictures[0].append(p1)
pictures[1].append(p2)
return pictures
def vidocr_to_csv(video,vcoords,tbcoords,f1app=True):
# inputs:
# video = video file as a string
# vcoords = array of pixel coordinates [top left x, top left y, bottom right x, bottom right y] for velocity
# tbcoords = array of pixel coordinates [top left x, top left y, bottom right x, bottom right y] for throttle/brake
# f1app = boolean, default = True, use True for video from the F1 app, False for onboard video.
# outputs .csv file with each line as a row of each extracted parameter.
# capture video via opencv
vid = cv2.VideoCapture(video)
s,frm = vid.read()
v_all = []
t_all = []
thr_all = []
brk_all = []
step = 1
total_frames = vid.get(cv2.CAP_PROP_FRAME_COUNT);
print(total_frames)
i = int(total_frames*0);
vid.set(0,i)
# go through each frame and extract data
while s:
if i >= int(total_frames):
break
s,frm = vid.read()
if i%step == 0 or i == total_frames-1:
v_temp = velocity_ocr(frm,vcoords,f1app)
t_temp = vid.get(cv2.CAP_PROP_POS_MSEC)/1e3
v_all += [v_temp]
# thr_temp = throttle_ocr(frm,tbcoords)
# brk_temp = brake_ocr(frm,tbcoords)
# thr_all += [thr_temp]
# brk_all += [brk_temp]
if i%200 == 0:
print(v_temp,t_temp,i)
i += 1
t_all = get_timestamps(video)
# save data to .csv with same filename as videofile
with open(video[0:-4]+'.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile)
writer.writerow(v_all)
writer.writerow(t_all)
# writer.writerow(thr_all)
# writer.writerow(brk_all)
writer.writerow([])
writer.writerow([])
print(video,"completed.")
