def tracking(self, verbose=True, video_path=None):
poses = []
init_frame = cv2.imread(self.frame_list[0])
#print(init_frame.shape)
init_gt = np.array(self.init_gt)
x1, y1, w, h = init_gt
init_gt = tuple(init_gt)
self.tracker.init(init_frame, init_gt)
writer = None
if verbose is True and video_path is not None:
writer = cv2.VideoWriter(
video_path, cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 30,
(init_frame.shape[1], init_frame.shape[0]))
for idx in range(len(self.frame_list)):
if idx != 0:
current_frame = cv2.imread(self.frame_list[idx])
height, width = current_frame.shape[:2]
start = time.time()
bbox = self.tracker.update(current_frame, vis=verbose)
print('track time', time.time() - start, current_frame.shape)
x1, y1, w, h = bbox
if verbose is True:
if len(current_frame.shape) == 2:
current_frame = cv2.cvtColor(current_frame,
cv2.COLOR_GRAY2BGR)
score = self.tracker.score
apce = APCE(score)
psr = PSR(score)
F_max = np.max(score)
size = self.tracker.crop_size
score = cv2.resize(score, size)
score -= score.min()
score = score / score.max()
score = (score * 255).astype(np.uint8)
# score = 255 - score
score = cv2.applyColorMap(score, cv2.COLORMAP_JET)
center = (int(x1 + w / 2), int(y1 + h / 2))
x0, y0 = center
x0 = np.clip(x0, 0, width - 1)
y0 = np.clip(y0, 0, height - 1)
center = (x0, y0)
xmin = int(center[0]) - size[0] // 2
xmax = int(center[0]) + size[0] // 2 + size[0] % 2
ymin = int(center[1]) - size[1] // 2
ymax = int(center[1]) + size[1] // 2 + size[1] % 2
left = abs(xmin) if xmin < 0 else 0
xmin = 0 if xmin < 0 else xmin
right = width - xmax
xmax = width if right < 0 else xmax
right = size[0] + right if right < 0 else size[0]
top = abs(ymin) if ymin < 0 else 0
ymin = 0 if ymin < 0 else ymin
down = height - ymax
ymax = height if down < 0 else ymax
down = size[1] + down if down < 0 else size[1]
score = score[top:down, left:right]
crop_img = current_frame[ymin:ymax, xmin:xmax]
score_map = cv2.addWeighted(crop_img, 0.6, score, 0.4, 0)
current_frame[ymin:ymax, xmin:xmax] = score_map
show_frame = cv2.rectangle(current_frame,
(int(x1), int(y1)),
(int(x1 + w), int(y1 + h)),
(255, 0, 0), 1)
"""
cv2.putText(show_frame, 'APCE:' + str(apce)[:5], (0, 250), cv2.FONT_HERSHEY_COMPLEX, 2,
(0, 0, 255), 5)
cv2.putText(show_frame, 'PSR:' + str(psr)[:5], (0, 300), cv2.FONT_HERSHEY_COMPLEX, 2,
(255, 0, 0), 5)
cv2.putText(show_frame, 'Fmax:' + str(F_max)[:5], (0, 350), cv2.FONT_HERSHEY_COMPLEX, 2,
(255, 0, 0), 5)
"""
cv2.imshow('demo', show_frame)
if writer is not None:
writer.write(show_frame)
cv2.waitKey(1)
poses.append(np.array([int(x1), int(y1), int(w), int(h)]))
return np.array(poses)
def tracking(self, verbose=True, video_path=None):
poses = []
init_frame = cv2.imread(self.frame_list[0])
init_gt = np.array(self.init_gt)
x1, y1, w, h = init_gt
init_gt = tuple(init_gt)
self.tracker.init(init_frame, init_gt)
writer = None
if verbose is True and video_path is not None:
writer = cv2.VideoWriter(
video_path, cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 30,
(init_frame.shape[1], init_frame.shape[0]))
fpss = []
ious = []
for i, (frame_name,
gt) in enumerate(zip(self.frame_list[1:], self.gts[1:])):
timer = cv2.getTickCount()
current_frame = cv2.imread(frame_name)
height, width = current_frame.shape[:2]
bbox = self.tracker.update(current_frame, vis=verbose)
if gt is not None:
iou = IOU(bbox, gt)
if iou < self.IOUmin:
break
ious.append(iou)
if i == 100:
print("Mean IOU (100 frames): {}".format(
sum(ious) / len(ious)))
x1, y1, w, h = bbox
if verbose:
if len(current_frame.shape) == 2:
current_frame = cv2.cvtColor(current_frame,
cv2.COLOR_GRAY2BGR)
score = self.tracker.score
apce = APCE(score)
psr = PSR(score)
F_max = np.max(score)
size = self.tracker.template_size
score = cv2.resize(score, size)
score -= score.min()
score = score / score.max()
score = (score * 255).astype(np.uint8)
# score = 255 - score
score = cv2.applyColorMap(score, cv2.COLORMAP_JET)
center = (int(x1 + w / 2), int(y1 + h / 2))
x0, y0 = center
x0 = np.clip(x0, 0, width - 1)
y0 = np.clip(y0, 0, height - 1)
center = (x0, y0)
xmin = int(center[0]) - size[0] // 2
xmax = int(center[0]) + size[0] // 2 + size[0] % 2
ymin = int(center[1]) - size[1] // 2
ymax = int(center[1]) + size[1] // 2 + size[1] % 2
left = abs(xmin) if xmin < 0 else 0
xmin = 0 if xmin < 0 else xmin
right = width - xmax
xmax = width if right < 0 else xmax
right = size[0] + right if right < 0 else size[0]
top = abs(ymin) if ymin < 0 else 0
ymin = 0 if ymin < 0 else ymin
down = height - ymax
ymax = height if down < 0 else ymax
down = size[1] + down if down < 0 else size[1]
score = score[top:down, left:right]
crop_img = current_frame[ymin:ymax, xmin:xmax]
score_map = cv2.addWeighted(crop_img, 0.6, score, 0.4, 0)
current_frame[ymin:ymax, xmin:xmax] = score_map
show_frame = cv2.rectangle(current_frame, (int(x1), int(y1)),
(int(x1 + w), int(y1 + h)),
(255, 0, 0), 1)
if gt is not None:
x0, y0, w0, h0 = gt
show_frame = cv2.rectangle(current_frame, (int(x1), int(y1)),
(int(x1 + w), int(y1 + h)),
(255, 0, 0), 1)
fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
fpss.append(fps)
cv2.putText(show_frame, "FPS : " + str(int(fps)), (100, 50),
cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50, 170, 50), 2)
"""
cv2.putText(show_frame, 'APCE:' + str(apce)[:5], (0, 250), cv2.FONT_HERSHEY_COMPLEX, 2,
(0, 0, 255), 5)
cv2.putText(show_frame, 'PSR:' + str(psr)[:5], (0, 300), cv2.FONT_HERSHEY_COMPLEX, 2,
(255, 0, 0), 5)
cv2.putText(show_frame, 'Fmax:' + str(F_max)[:5], (0, 350), cv2.FONT_HERSHEY_COMPLEX, 2,
(255, 0, 0), 5)
"""
cv2.imshow('demo', show_frame)
if writer is not None:
writer.write(show_frame)
cv2.waitKey(1)
poses.append(np.array([int(x1), int(y1), int(w), int(h)]))
print("FPS: " + str(sum(fpss) / len(fpss)))
print("Lost after {} frames".format(len(ious)))
return np.array(poses)
def tracking(self,verbose=True,video_path=None):
poses = []
# Initial Frame, reading through frame_list
init_frame = cv2.imread(self.frame_list[0])
# print(init_frame.shape)
init_gt = np.array(self.init_gt)
# coordinates of centre, width and height
x1, y1, w, h = init_gt
init_gt=tuple(init_gt)
# Input to the tracker
self.tracker.init(init_frame,init_gt)
writer=None
# Writing the file into a video if video path is available
if verbose is True and video_path is not None:
writer = cv2.VideoWriter(video_path, cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 30, (init_frame.shape[1], init_frame.shape[0]))
# Traversing over the list of frames
for idx in range(len(self.frame_list)):
if idx != 0:
# Reading the frame at the current index
current_frame=cv2.imread(self.frame_list[idx])
height,width=current_frame.shape[:2]
# Calling the update method of the tracker class.
'''
UPDATE METHOD:
INPUT:
a) current_frame
b) verbose
OUTPUT:
bbox coordinates in this frame.
'''
bbox=self.tracker.update(current_frame, vis=verbose)
x1,y1,w,h=bbox
#
if verbose is True:
if len(current_frame.shape)==2:
current_frame=cv2.cvtColor(current_frame,cv2.COLOR_GRAY2BGR)
score = self.tracker.score
apce = APCE(score)
psr = PSR(score)
F_max = np.max(score)
size=self.tracker.crop_size
score = cv2.resize(score, size)
score -= score.min()
score =score/ score.max()
score = (score * 255).astype(np.uint8)
# score = 255 - score
score = cv2.applyColorMap(score, cv2.COLORMAP_JET)
center = (int(x1+w/2),int(y1+h/2))
x0,y0=center
x0=np.clip(x0,0,width-1)
y0=np.clip(y0,0,height-1)
center=(x0,y0)
xmin = int(center[0]) - size[0] // 2
xmax = int(center[0]) + size[0] // 2 + size[0] % 2
ymin = int(center[1]) - size[1] // 2
ymax = int(center[1]) + size[1] // 2 + size[1] % 2
left = abs(xmin) if xmin < 0 else 0
xmin = 0 if xmin < 0 else xmin
right = width - xmax
xmax = width if right < 0 else xmax
right = size[0] + right if right < 0 else size[0]
top = abs(ymin) if ymin < 0 else 0
ymin = 0 if ymin < 0 else ymin
down = height - ymax
ymax = height if down < 0 else ymax
down = size[1] + down if down < 0 else size[1]
score = score[top:down, left:right]
crop_img = current_frame[ymin:ymax, xmin:xmax]
score_map = cv2.addWeighted(crop_img, 0.6, score, 0.4, 0)
current_frame[ymin:ymax, xmin:xmax] = score_map
show_frame=cv2.rectangle(current_frame, (int(x1), int(y1)), (int(x1 + w), int(y1 + h)), (255, 0, 0),1)
"""
cv2.putText(show_frame, 'APCE:' + str(apce)[:5], (0, 250), cv2.FONT_HERSHEY_COMPLEX, 2,
(0, 0, 255), 5)
cv2.putText(show_frame, 'PSR:' + str(psr)[:5], (0, 300), cv2.FONT_HERSHEY_COMPLEX, 2,
(255, 0, 0), 5)
cv2.putText(show_frame, 'Fmax:' + str(F_max)[:5], (0, 350), cv2.FONT_HERSHEY_COMPLEX, 2,
(255, 0, 0), 5)
"""
cv2.imshow('demo', show_frame)
if writer is not None:
writer.write(show_frame)
cv2.waitKey(1)
poses.append(np.array([int(x1), int(y1), int(w), int(h)]))
return np.array(poses)