python LK光流金字塔的猜测光流

本文整理汇总了Python中cv2.calcOpticalFlowFarneback方法的典型用法代码示例。如果您正苦于以下问题：Python cv2.calcOpticalFlowFarneback方法的具体用法？Python cv2.calcOpticalFlowFarneback怎么用？Python cv2.calcOpticalFlowFarneback使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在模块cv2的用法示例。

在下文中一共展示了cv2.calcOpticalFlowFarneback方法的16个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: compute_dense_optical_flow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def compute_dense_optical_flow(prev_image, current_image):
 old_shape = current_image.shape
 prev_image_gray = cv2.cvtColor(prev_image, cv2.COLOR_BGR2GRAY)
 current_image_gray = cv2.cvtColor(current_image, cv2.COLOR_BGR2GRAY)
 assert current_image.shape == old_shape
 hsv = np.zeros_like(prev_image)
 hsv[…, 1] = 255
 flow = None
 flow = cv2.calcOpticalFlowFarneback(prev=prev_image_gray,
 next=current_image_gray, flow=flow,
 pyr_scale=0.8, levels=15, winsize=5,
 iterations=10, poly_n=5, poly_sigma=0,
 flags=10)
 mag, ang = cv2.cartToPolar(flow[…, 0], flow[…, 1])
 hsv[…, 0] = ang * 180 / np.pi / 2
 hsv[…, 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
 return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
 开发者ID:ferreirafabio，项目名称:video2tfrecord，代码行数:20，代码来源:video2tfrecord.py示例2: compute_opticalflow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def compute_opticalflow(prev_image, cur_image, args):
 prev_gray = cv2.cvtColor(prev_image, cv2.COLOR_RGB2GRAY)
 cur_gray = cv2.cvtColor(cur_image, cv2.COLOR_RGB2GRAY)
 pyr_scale = args.pyr_scale
 pyr_levels = args.pyr_levels
 winsize = args.winsize
 iterations = args.iterations
 poly_n = args.poly_n
 poly_sigma = args.poly_sigma
 flow = cv2.calcOpticalFlowFarneback(prev_gray, cur_gray, flow=None,
 pyr_scale=pyr_scale,
 levels=pyr_levels,
 iterations=iterations,
 winsize=winsize,
 poly_n=poly_n,
 poly_sigma=poly_sigma,
 flags=0)
 return flow
 开发者ID:linjieyangsc，项目名称:video_seg，代码行数:20，代码来源:image_util.py示例3: run_farneback
需要导入模块: import cv2 [as 别名]
或者: from cv2 import calcOpticalFlowFarneback [as 别名]
def run_farneback(frames):
 try:
 return cv2.calcOpticalFlowFarneback(
 frames[0], frames[1],
 # options, defaults
 None, # output
 0.5, # pyr_scale, 0.5
 10, # levels, 3
 min(frames[0].shape[:2]) // 5, # winsize, 15
 10, # iterations, 3
 7, # poly_n, 5
 1.5, # poly_sigma, 1.2
 cv2.OPTFLOW_FARNEBACK_GAUSSIAN, # flags, 0
 )
 except cv2.error:
 return None
 开发者ID:facebookresearch，项目名称:DetectAndTrack，代码行数:18，代码来源:tracking_engine.py示例4: denseOpticalFlow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def denseOpticalFlow():
 # use 0 for webcam capturing
 # cap = cv2.VideoCapture(0)
 cap = cv2.VideoCapture(‘test/Pedestrian overpass.mp4’)
 ret, frame1 = cap.read()
 prvs = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)
 hsv = np.zeros_like(frame1)
 hsv[…,1] = 255
 while(1):
 ret, frame2 = cap.read()
 next = cv2.cvtColor(frame2,cv2.COLOR_BGR2GRAY)
 flow = cv2.calcOpticalFlowFarneback(prvs,next, None, 0.5, 3, 15, 3, 5, 1.2, 0)
 mag, ang = cv2.cartToPolar(flow[…,0], flow[…,1])
 hsv[…,0] = ang*180/np.pi/2
 hsv[…,2] = cv2.normalize(mag,None,0,255,cv2.NORM_MINMAX)
 # print(np.sum(mag[100:300, 100:300]))
 if (np.sum(mag)> 100000):
 print(‘motion detected’)
 bgr = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR)
 cv2.imshow(‘frame2’,bgr)
 k = cv2.waitKey(30) & 0xff
 if k == 27:
 break
 elif k == ord(‘s’):
 cv2.imwrite(‘opticalfb.png’,frame2)
 cv2.imwrite(‘opticalhsv.png’,bgr)
 prvs = next
 cap.release()
 cv2.destroyAllWindows()
 开发者ID:sahibdhanjal，项目名称:Mask-RCNN-Pedestrian-Detection，代码行数:38，代码来源:opticalFlow.py示例5: extract_optical_flow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def extract_optical_flow(fn, times, frames=8, scale_factor=1.0):
 cap = cv2.VideoCapture(fn)
 n_frames = cap.get(cv2.CAP_PROP_FRAME_COUNT)
 outputs = []
 if n_frames < frames * 2:
 return outputs
 def resize(im):
 if scale_factor != 1.0:
 new_size = (int(im.shape[1] * scale_factor), int(im.shape[0] * scale_factor))
 return cv2.resize(im, new_size, interpolation=cv2.INTER_LINEAR)
 else:
 return im
 for t in times:
 cap.set(cv2.CAP_PROP_POS_FRAMES, min(t * n_frames, n_frames - 1 - frames))
 ret, frame0 = cap.read()
 im0 = resize(cv2.cvtColor(frame0, cv2.COLOR_BGR2GRAY))
 mags = []
 middle_frame = frame0
 for f in range(frames - 1):
 ret, frame1 = cap.read()
 if f == frames // 2:
 middle_frame = frame1
 im1 = resize(cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY))
 flow = cv2.calcOpticalFlowFarneback(im0, im1,
 None, 0.5, 3, 15, 3, 5, 1.2, 0)
 mag, ang = cv2.cartToPolar(flow[…,0], flow[…,1])
 mags.append(mag)
 im0 = im1
 mag = np.sum(mags, 0)
 mag = mag.clip(min=0)
 norm_mag = (mag - mag.min()) / (mag.max() - mag.min() + 1e-5)
 x = middle_frame[…, ::-1].astype(np.float32) / 255
 outputs.append((x, norm_mag))
 return outputs
 开发者ID:gustavla，项目名称:self-supervision，代码行数:38，代码来源:video_avi_flow_saliency.py示例6: extract_optical_flow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def extract_optical_flow(fn, n_frames=34):
 img = dd.image.load(fn)
 if img.shape != (128*34, 128, 3):
 return []
 frames = np.array_split(img, 34, axis=0)
 grayscale_frames = [fr.mean(-1) for fr in frames]
 mags = []
 skip_frames = np.random.randint(34 - n_frames + 1)
 middle_frame = frames[np.random.randint(skip_frames, skip_frames+n_frames)]
 im0 = grayscale_frames[skip_frames]
 for f in range(1+skip_frames, 1+skip_frames+n_frames-1):
 im1 = grayscale_frames[f]
 flow = cv2.calcOpticalFlowFarneback(im0, im1,
 None, # flow
 0.5, # pyr_scale
 3, # levels
 np.random.randint(3, 20), # winsize
 3, #iterations
 5, #poly_n
 1.2, #poly_sigma
 0 # flags
 )
 mag, ang = cv2.cartToPolar(flow[…,0], flow[…,1])
 mags.append(mag)
 im0 = im1
 mag = np.sum(mags, 0)
 mag = mag.clip(min=0)
 #norm_mag = np.tanh(mag * 10000)
 norm_mag = (mag - mag.min()) / (mag.max() - mag.min() + 1e-5)
 outputs = []
 outputs.append((middle_frame, norm_mag))
 return outputs
 开发者ID:gustavla，项目名称:self-supervision，代码行数:34，代码来源:video_jpeg_rolls_flow_saliency.py示例7: MFMGetFM

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def MFMGetFM(self, src):
 # convert scale
 I8U = np.uint8(255 * src)
 cv2.waitKey(10)
 # calculating optical flows
 if self.prev_frame is not None:
 farne_pyr_scale = pySaliencyMapDefs.farne_pyr_scale
 farne_levels = pySaliencyMapDefs.farne_levels
 farne_winsize = pySaliencyMapDefs.farne_winsize
 farne_iterations = pySaliencyMapDefs.farne_iterations
 farne_poly_n = pySaliencyMapDefs.farne_poly_n
 farne_poly_sigma = pySaliencyMapDefs.farne_poly_sigma
 farne_flags = pySaliencyMapDefs.farne_flags
 flow = cv2.calcOpticalFlowFarneback(
 prev=self.prev_frame,
 next=I8U,
 pyr_scale=farne_pyr_scale,
 levels=farne_levels,
 winsize=farne_winsize,
 iterations=farne_iterations,
 poly_n=farne_poly_n,
 poly_sigma=farne_poly_sigma,
 flags=farne_flags,
 flow=None
 )
 flowx = flow[…, 0]
 flowy = flow[…, 1]
 else:
 flowx = np.zeros(I8U.shape)
 flowy = np.zeros(I8U.shape)
 # create Gaussian pyramids
 dst_x = self.FMGaussianPyrCSD(flowx)
 dst_y = self.FMGaussianPyrCSD(flowy)
 # update the current frame
 self.prev_frame = np.uint8(I8U)
 # return
 return dst_x, dst_y
 # conspicuity maps
 # standard range normalization

开发者ID:tyarkoni，项目名称:pliers，代码行数:42，代码来源:pySaliencyMap.py

示例8: optic_flow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def optic_flow(mov, tmpl, nflows):
 “”" optic flow computation using farneback “”"
 window = int(1 / 0.2) # window size
 nframes, Ly, Lx = mov.shape
 mov = mov.astype(np.float32)
 mov = np.reshape(mov[:int(np.floor(nframes/window)*window),:,:],
 (-1,window,Ly,Lx)).mean(axis=1)
 mov = mov[np.random.permutation(mov.shape[0])[:min(nflows,mov.shape[0])], :, :]
 pyr_scale=.5
 levels=3
 winsize=100
 iterations=15
 poly_n=5
 poly_sigma=1.2 / 5
 flags=0
 nframes, Ly, Lx = mov.shape
 norms = np.zeros((nframes,))
 flows = np.zeros((nframes,Ly,Lx,2))
 for n in range(nframes):
 flow = cv2.calcOpticalFlowFarneback(
 tmpl, mov[n,:,:], None, pyr_scale, levels, winsize, iterations, poly_n, poly_sigma, flags)
 flows[n,:,:,:] = flow
 norms[n] = ((flow**2).sum()) ** 0.5
 return flows, norms

开发者ID:MouseLand，项目名称:suite2p，代码行数:32，代码来源:metrics.py

示例9: get_direction

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def get_direction(self, frame1, frame2, show=False):
 frame1 = cv2.resize(frame1, (self.width, self.height))
 frame1 = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)
 frame2 = cv2.resize(frame2, (self.width, self.height))
 frame2 = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
 flow = cv2.calcOpticalFlowFarneback(frame1[self.height_start:self.height_end],
 frame2[self.height_start:self.height_end], None, 0.5, 3, 15, 1, 5, 1.2, 0)
 flow_avg = np.median(flow, axis=(0, 1)) # [x, y]
 move_x = -1 * flow_avg[0]
 move_y = -1 * flow_avg[1]
 if show:
 hsv = np.zeros((self.height_end - self.height_start, self.width, 3))
 hsv[…,1] = 255
 mag, ang = cv2.cartToPolar(flow[…, 0], flow[…, 1])
 hsv[…, 0] = ang * 180 / np.pi / 2
 hsv[…, 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
 bgr = cv2.cvtColor(np.array(hsv).astype(np.uint8), cv2.COLOR_HSV2BGR)
 cv2.imshow(‘opt_flow’, bgr)
 if cv2.waitKey(1) & 0xFF == ord(‘q’):
 print(‘User Interrupted’)
 exit(1)
 return move_x, move_y

开发者ID:YoongiKim，项目名称:Walk-Assistant，代码行数:29，代码来源:opt_flow.py

示例10: _calc_optical_flow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def calc_optical_flow(prev, next):
 flow = cv2.calcOpticalFlowFarneback(prev, next_, flow=None, pyr_scale=0.5, levels=3, winsize=15, iterations=3,
 poly_n=5, poly_sigma=1.2, flags=0)
 return flow

开发者ID:woodfrog，项目名称:ActionRecognition，代码行数:6，代码来源:OF_utils.py

示例11: dense_flow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def dense_flow(image):
 global prvs
 next = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
 flow = cv2.calcOpticalFlowFarneback(prvs, next, None, 0.5, 3, 15, 3, 5, 1.2, 0)
 mag, ang = cv2.cartToPolar(flow[…, 0], flow[…, 1])
 hsv[…, 0] = ang * 180 / np.pi / 2
 hsv[…, 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
 image = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
 prvs = next
 return image

开发者ID:charlielito，项目名称:snapchat-filters-opencv，代码行数:15，代码来源:dense_optflow.py

示例12: next

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def next(self, arImage:np.array) -> np.array:
 # first?
 if self.arPrev.shape == (1,1): return self.first(arImage)
 # get image in black&white
 arCurrent = cv2.cvtColor(arImage, cv2.COLOR_BGR2GRAY)
 if self.sAlgorithm == “tvl1”:
 arFlow = self.oTVL1.calc(self.arPrev, arCurrent, None)
 elif self.sAlgorithm == “farnback”:
 arFlow = cv2.calcOpticalFlowFarneback(self.arPrev, arCurrent, flow=None,
 pyr_scale=0.5, levels=1, winsize=15, iterations=2, poly_n=5, poly_sigma=1.1, flags=0)
 else: raise ValueError(“Unknown optical flow type”)
 # only 2 dims
 arFlow = arFlow[:, :, 0:2]
 # truncate to +/-15.0, then rescale to [-1.0, 1.0]
 arFlow[arFlow > self.fBound] = self.fBound
 arFlow[arFlow < -self.fBound] = -self.fBound
 arFlow = arFlow / self.fBound
 if self.bThirdChannel:
 # add third empty channel
 arFlow = np.concatenate((arFlow, self.arZeros), axis=2)
 self.arPrev = arCurrent
 return arFlow

开发者ID:FrederikSchorr，项目名称:sign-language，代码行数:32，代码来源:opticalflow.py

示例13: extract_optical_flow

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def extract_optical_flow(fn, times, frames=8, scale_factor=1.0):
 cap = cv2.VideoCapture(fn)
 if not cap.isOpened():
 return []
 n_frames = cap.get(cv2.CAP_PROP_FRAME_COUNT)
 outputs = []
 if n_frames < frames * 2:
 return outputs
 def resize(im):
 if scale_factor != 1.0:
 new_size = (int(im.shape[1] * scale_factor), int(im.shape[0] * scale_factor))
 return cv2.resize(im, new_size, interpolation=cv2.INTER_LINEAR)
 else:
 return im
 for t in times:
 cap.set(cv2.CAP_PROP_POS_FRAMES, min(t * n_frames, n_frames - 1 - frames))
 ret, frame0 = cap.read()
 im0 = resize(cv2.cvtColor(frame0, cv2.COLOR_BGR2GRAY))
 mags = []
 middle_frame = frame0
 flows = []
 for f in range(frames - 1):
 ret, frame1 = cap.read()
 if f == frames // 2:
 middle_frame = frame1
 im1 = resize(cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY))
 flow = cv2.calcOpticalFlowFarneback(im0, im1,
 None,
 0.5, # py_scale
 8, # levels
 int(40 * scale_factor), # winsize
 10, # iterations
 5, # poly_n
 1.1, # poly_sigma
 cv2.OPTFLOW_FARNEBACK_GAUSSIAN)
 #mag, ang = cv2.cartToPolar(flow[…,0], flow[…,1])
 #mags.append(mag)
 flows.append(flow)
 im0 = im1
 flow = (np.mean(flows, 0) / 100).clip(-1, 1)
 #flow = np.mean(flows, 0)
 #flow /= (flow.mean() * 5 + 1e-5)
 #flow = flow.clip(-1, 1)
 #flows = flows / (np.mean(flows, 0, keepdims=True) + 1e-5)
 x = middle_frame[…, ::-1].astype(np.float32) / 255
 outputs.append((x, flow))
 return outputs

开发者ID:gustavla，项目名称:self-supervision，代码行数:52，代码来源:video_avi_flow.py

示例14: run_parameter

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def run_parameter(config_item):
 prev_img = cv2.imread(config_item[“files”][“prevImg”])
 curr_img = cv2.imread(config_item[“files”][“currImg”])
 flow_method = config_item[“parameter”][“flow_method”]
 estimate_base = config_item[“files”][“estimatepath”] + “/”
 if os.path.exists(estimate_base) == False:
 os.makedirs(estimate_base)
 if os.path.exists(config_item[“files”][“estflow”]):
 return
 # compute optical flow
 if flow_method.find(“dual”) >= 0:
 dual_proc = cv2.DualTVL1OpticalFlow_create(config_item[“parameter”][“tau”],
 config_item[“parameter”][“lambda”],
 config_item[“parameter”][“theta”],
 config_item[“parameter”][“nscales”],
 config_item[“parameter”][“warps”])
 est_flow = np.zeros(shape=(prev_img.shape[0], prev_img.shape[1],2), dtype=np.float32)
 dual_proc.calc(cv2.cvtColor(prev_img, cv2.COLOR_BGR2GRAY), cv2.cvtColor(curr_img, cv2.COLOR_BGR2GRAY), est_flow)
 #
 elif flow_method.find(“farneback”) >= 0:
 est_flow = cv2.calcOpticalFlowFarneback(cv2.cvtColor(prev_img, cv2.COLOR_BGR2GRAY),
 cv2.cvtColor(curr_img, cv2.COLOR_BGR2GRAY),
 None, 0.5, 3, 15, 3, 5, 1.2, 0)
 elif flow_method.find(“plk”) >= 0:
 prev_pts = list()
 for r in range(prev_img.shape[0]):
 for c in range(prev_img.shape[1]):
 prev_pts.append((c,r))
 prev_pts = np.array(prev_pts, dtype=np.float32)
 curr_pts, st, err = cv2.calcOpticalFlowPyrLK(cv2.cvtColor(prev_img, cv2.COLOR_BGR2GRAY),
 cv2.cvtColor(curr_img, cv2.COLOR_BGR2GRAY),
 prev_pts, None,
 winSize=(21,21), maxLevel=3, criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 20, 0.001))
 est_flow = np.zeros(shape=(prev_img.shape[0], prev_img.shape[1],2), dtype=np.float32)
 n = 0
 flow_pts = curr_pts - prev_pts
 for r in range(prev_img.shape[0]):
 for c in range(prev_img.shape[1]):
 est_flow[r, c, :] = flow_pts[n,:]
 n = n + 1
 #here alternative optical flow methods can be applied
 #
 else:
 raise ValueError(“flow method has not been implemented”)
 ut.writeFlowFile(config_item[“files”][“estflow”], est_flow)
 ut.drawFlowField(config_item[“files”][“estflow”][:-3] + “png”, est_flow)
 print("Done -> ", config_item[“files”][“estflow”])

开发者ID:tsenst，项目名称:CrowdFlow，代码行数:52，代码来源:opticalflow_estimate.py

示例15: processFrame

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def processFrame(self, frame, distance=None, timestep=1):
 ‘’’
 Processes one image frame, returning summed X,Y flow and frame.
 Optional inputs are:
 distance - distance in meters to image (focal length) for returning flow in meters per second
 timestep - time step in seconds for returning flow in meters per second
 ‘’’
 frame2 = cv2.resize(frame, self.size)
 gray = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
 xsum, ysum = 0,0
 xvel, yvel = 0,0
 flow = None
 if not self.prev_gray is None:
 flow = cv2.calcOpticalFlowFarneback(self.prev_gray, gray, flow, pyr_scale=0.5, levels=5, winsize=13, iterations=10, poly_n=5, poly_sigma=1.1, flags=0)
 for y in range(0, flow.shape[0], self.move_step):
 for x in range(0, flow.shape[1], self.move_step):
 fx, fy = flow[y, x]
 xsum += fx
 ysum += fy
 cv2.line(frame2, (x,y), (int(x+fx),int(y+fy)), self.mv_color_bgr)
 cv2.circle(frame2, (x,y), 1, self.mv_color_bgr, -1)
 # Default to system time if no timestep
 curr_time = time.time()
 if not timestep:
 timestep = (curr_time - self.prev_time) if self.prev_time else 1
 self.prev_time = curr_time
 xvel = self._get_velocity(flow, xsum, flow.shape[1], distance, timestep)
 yvel = self._get_velocity(flow, ysum, flow.shape[0], distance, timestep)
 self.prev_gray = gray
 if self.window_name:
 cv2.imshow(self.window_name, frame2)
 if cv2.waitKey(1) & 0x000000FF== 27: # ESC
 return None
 # Return x,y velocities and new image with flow lines
 return xvel, yvel, frame2
 开发者ID:simondlevy，项目名称:OpenCV-Python-Hacks，代码行数:55，代码来源:init.py

示例16: MFMGetFM

需要导入模块: import cv2 [as 别名]

或者: from cv2 import calcOpticalFlowFarneback [as 别名]

def MFMGetFM(self, src):
 # Convert scale
 I8U = np.uint8(255 * src)
 # cv2.waitKey(10)
 # Calculating optical flows
 if self.prev_frame is not None:
 farne_pyr_scale = pySaliencyMapDefs.farne_pyr_scale
 farne_levels = pySaliencyMapDefs.farne_levels
 farne_winsize = pySaliencyMapDefs.farne_winsize
 farne_iterations = pySaliencyMapDefs.farne_iterations
 farne_poly_n = pySaliencyMapDefs.farne_poly_n
 farne_poly_sigma = pySaliencyMapDefs.farne_poly_sigma
 farne_flags = pySaliencyMapDefs.farne_flags
 flow = cv2.calcOpticalFlowFarneback( 
 prev=self.prev_frame, 
 next=I8U, 
 pyr_scale=farne_pyr_scale, 
 levels=farne_levels, 
 winsize=farne_winsize, 
 iterations=farne_iterations, 
 poly_n=farne_poly_n, 
 poly_sigma=farne_poly_sigma, 
 flags=farne_flags, 
 flow=None 
 )
 flowx = flow[…, 0]
 flowy = flow[…, 1]
 else:
 flowx = np.zeros(I8U.shape)
 flowy = np.zeros(I8U.shape)
 # Create Gaussian pyramids
 dst_x = self.FMGaussianPyrCSD(flowx)
 dst_y = self.FMGaussianPyrCSD(flowy)
 # Update the current frame
 self.prev_frame = np.uint8(I8U)
 return dst_x, dst_y
 # Conspicuity maps
 # Standard range normalization
 开发者ID:aalto-ui，项目名称:aim，代码行数:45，代码来源:pySaliencyMap.py