def __data_generation(self, seVideo: pd.Series) -> (np.array(float), int):
"Returns frames for 1 video, including normalizing & preprocessing"
# Get the frames from disc
ar_nFrames = files2frames(seVideo.sFrameDir)
#print(ar_nFrames.shape)
#scipy.misc.imsave('outfile.jpg', ar_nFrames[0])
#scipy.misc.imsave('outfile_flip.jpg', np.fliplr(ar_nFrames[0]))
ar_nFrames_flip = np.array(
[np.fliplr(ar_nFrames[i]) for i in range(ar_nFrames.shape[0])])
# only use the first nChannels (typically 3, but maybe 2 for optical flow)
ar_nFrames = ar_nFrames[..., 0:self.nChannels]
ar_nFrames_flip = ar_nFrames_flip[..., 0:self.nChannels]
ar_nFrames = images_normalize(ar_nFrames,
self.nFrames,
self.nHeight,
self.nWidth,
bRescale=True)
ar_nFrames_flip = images_normalize(ar_nFrames_flip,
self.nFrames,
self.nHeight,
self.nWidth,
bRescale=True)
self.prv_frame = ar_nFrames
self.prv_frame_flip = ar_nFrames_flip
return ar_nFrames, seVideo.nLabel, ar_nFrames_flip, seVideo.nLabel
def __data_generation(self, seVideo:pd.Series) -> (np.array(float), int):
"Returns frames for 1 video, including normalizing & preprocessing"
# Get the frames from disc
ar_nFrames = files2frames(seVideo.sFrameDir)
# only use the first nChannels (typically 3, but maybe 2 for optical flow)
ar_nFrames = ar_nFrames[..., 0:self.nChannels]
ar_fFrames = images_normalize(ar_nFrames, self.nFrames, self.nHeight, self.nWidth, bRescale = True)
return ar_fFrames, seVideo.nLabel
def video_capture(oStream, sColor, sText, tuRectangle = (224, 224), nTimeDuration = 3, bOpticalFlow = False) -> \
(float, np.array, np.array):
if bOpticalFlow:
oOpticalFlow = OpticalFlow(bThirdChannel=False)
liFrames = []
liFlows = []
fTimeStart = time.time()
# loop over frames from the video file stream
while True:
# grab the frame from the threaded video file stream
(bGrabbed, arFrame) = oStream.read()
arFrame = rescale_frame(arFrame, 320, 240)
arFrame = cv2.flip(arFrame, 1)
liFrames.append(arFrame)
fTimeElapsed = time.time() - fTimeStart
s = sText + str(int(fTimeElapsed) + 1) + " sec"
# paint rectangle & text, show the frame
arFrameText = rectangle_text(arFrame, sColor, s, "", tuRectangle)
cv2.imshow("Video", arFrameText)
# display optical flow
if bOpticalFlow:
arFlow = oOpticalFlow.next(image_crop(arFrame, *tuRectangle))
liFlows.append(arFlow)
h, w, _ = arFlow.shape
arZeros = np.zeros((h, w, 1), dtype=np.float32)
arFlow = np.concatenate((arFlow, arZeros), axis=2)
cv2.imshow("Optical flow", flow2colorimage(arFlow))
# stop after nTimeDuration sec
if fTimeElapsed >= nTimeDuration: break
# Press 'q' for early exit
key = cv2.waitKey(1) #& 0xFF
if key == ord('q'): break
#cv2.waitKey(1)
if key == 114 or key == 100:
break
return fTimeElapsed, images_normalize(np.array(liFrames), 40, 224, 224,
True), np.array(liFlows), key