def visualize(self):
frame = self.frame
font = cv2.FONT_HERSHEY_DUPLEX
line_type = cv2.LINE_AA
# draw and label blob bounding boxes
for _id, blob in self.blobs.items():
(x, y, w, h) = [int(v) for v in blob.bounding_box]
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
vehicle_label = 'I: ' + _id[:8] \
if blob.type is None \
else 'I: {0}, T: {1} ({2})'.format(_id[:8], blob.type, str(blob.type_confidence)[:4])
cv2.putText(frame, vehicle_label, (x, y - 5), font, 1, (255, 0, 0),
2, line_type)
# draw counting lines
for counting_line in self.counting_lines:
cv2.line(frame, counting_line['line'][0], counting_line['line'][1],
(255, 0, 0), 3)
cl_label_origin = (counting_line['line'][0][0],
counting_line['line'][0][1] + 35)
cv2.putText(frame, counting_line['label'], cl_label_origin, font,
1, (255, 0, 0), 2, line_type)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi)
return frame
def visualize(self):
frame = self.frame
# draw and label blob bounding boxes
for _id, blob in self.blobs.items():
(x, y, w, h) = [int(v) for v in blob.bounding_box]
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
vehicle_label = 'ID: ' + _id[:8] \
if blob.type == None \
else 'ID: {0}, Type: {1} ({2})'.format(_id[:8], blob.type, str(blob.type_confidence)[:4])
cv2.putText(frame, vehicle_label, (x, y - 5),
cv2.FONT_HERSHEY_DUPLEX, 1.2, (255, 0, 0), 2,
cv2.LINE_AA)
# draw counting line
if self.counting_line != None:
cv2.line(frame, self.counting_line[0], self.counting_line[1],
(255, 0, 0), 3)
# display vehicle count
types_counts_str = ', '.join(
[': '.join(map(str, i)) for i in self.types_counts.items()])
types_counts_str = ' (' + types_counts_str + ')' if types_counts_str != '' else types_counts_str
cv2.putText(frame,
'Count: ' + str(self.vehicle_count) + types_counts_str,
(20, 60), cv2.FONT_HERSHEY_DUPLEX, 1.5, (255, 0, 0), 2,
cv2.LINE_AA)
cv2.putText(
frame,
'Processing speed: ' + str(self.processing_frame_rate) + ' FPS',
(20, 120), cv2.FONT_HERSHEY_DUPLEX, 1.5, (255, 0, 0), 2,
cv2.LINE_AA)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi)
return frame
def visualize(self):
frame = self.frame
# draw and label blob bounding boxes
for _id, blob in self.blobs.items():
(x, y, w, h) = [int(v) for v in blob.bounding_box]
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
a = (2 * x + w) / 2 # x,y更新了？
b = (2 * y + h) / 2
#blob.center = ([a, b])
vehicle_label = 'ID: ' + _id[:8] \
if blob.type == None else 'Type: {0} ({1})'.format( blob.type, str(blob.type_confidence)[:4])
#else 'ID: {0}, Type: {1} ({2})'.format(_id[:8], blob.type, str(blob.type_confidence)[:4])
# change
#file = open(_id+r".txt", "a")
#point2 = (a+300, b+300)
#points=np.loadtxt(_id + r".txt")
#新添加的
path=r"D:\ZHOUSHENGHUA\Vehicle-Counting-master\Location"+'\\'+_id+r".txt"
if os.path.exists(path):
trace=np.append(np.loadtxt(path, delimiter=','),np.array([[a,b]]),axis=0,)
recent_trace=trace[np.size(trace,0)-5:np.size(trace,0),:]
print (recent_trace)
np.savetxt(path, trace,delimiter=',')
#print (trace)
cv2.polylines(frame, np.int32([trace]), 0, (0, 0, 255),2)
else:
data=np.array([[a,b],[a,b]])
np.savetxt(path, data, delimiter=',')
# 新添加的
# points = np.array(blob.center)
#points=np.append([blob.center],[point2],axis=0)
#points.append(blob.center,)
#points.append([100,100])
# points.dtype => 'int64'
#np.int32([points])
cv2.putText(frame, vehicle_label, (x, y - 5), cv2.FONT_HERSHEY_DUPLEX, 0.3, (255, 0, 0), 1, cv2.LINE_AA) #0.3字体大小，0.5字体粗细
#cv2.polylines(frame,[(300,300), (100,100),(200,500)], 0, (0, 0, 255))
# draw counting line
if self.counting_line != None:
cv2.line(frame, self.counting_line[0], self.counting_line[1], (255, 0, 0), 3)
# display vehicle count
types_counts_str = ', '.join([': '.join(map(str, i)) for i in self.types_counts.items()])
types_counts_str = ' (' + types_counts_str + ')' if types_counts_str != '' else types_counts_str
cv2.putText(frame, 'Count: ' + str(self.vehicle_count) + types_counts_str, (20, 60), cv2.FONT_HERSHEY_DUPLEX, 0.5, (255, 0, 0), 1, cv2.LINE_AA)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi)
return frame
def visualize(self):
frame = self.frame
font = cv2.FONT_HERSHEY_DUPLEX
line_type = cv2.LINE_AA
# draw and label blob bounding boxes
for _id, blob in self.blobs.items():
(x, y, w, h) = [int(v) for v in blob.bounding_box]
cv2.rectangle(frame, (x, y), (x + w, y + h), self.hud_color, 2)
object_label = 'I: ' + _id[:8] \
if blob.type is None \
else 'I: {0}, T: {1} ({2})'.format(_id[:8], blob.type, str(blob.type_confidence)[:4])
cv2.putText(frame, object_label, (x, y - 5), font, 1,
self.hud_color, 2, line_type)
# draw counting lines
for counting_line in self.counting_lines:
p0 = counting_line['line'][0]
p1 = counting_line['line'][1]
cv2.line(frame, p0, p1, self.hud_color, 3)
direction = counting_line.get('direction', None)
if direction == 'left' or direction == 'right':
p0_ = np.array(p0)
p1_ = np.array(p1)
if direction == 'left':
pd_ = (p0_ + p1_) / 2 + ccw_rot.dot((p1_ - p0_) / 10)
else:
pd_ = (p0_ + p1_) / 2 - ccw_rot.dot((p1_ - p0_) / 10)
pd = (int(pd_[0]), int(pd_[1]))
cv2.line(frame, p0, pd, self.hud_color, 1)
cv2.line(frame, p1, pd, self.hud_color, 1)
cl_label_origin = (counting_line['line'][0][0],
counting_line['line'][0][1] + 35)
cv2.putText(frame, counting_line['label'], cl_label_origin, font,
1, self.hud_color, 2, line_type)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi)
# show counts
if self.show_counts:
offset = 1
for line, objects in self.counts.items():
cv2.putText(frame, line, (10, 40 * offset), font, 1,
self.hud_color, 2, line_type)
for label, count in objects.items():
offset += 1
cv2.putText(frame, "{}: {}".format(label, count),
(10, 40 * offset), font, 1, self.hud_color, 2,
line_type)
offset += 2
return frame
def visualize(self):
frame = self.frame
font = cv2.FONT_HERSHEY_DUPLEX
line_type = cv2.LINE_AA
colors = [(255, 255, 255), (255, 255, 0), (255, 0, 0), (255, 0, 255),
(0, 255, 255), (0, 255, 0), (0, 255, 255)]
color_i = 0
# draw and label blob bounding boxes
for _id, blob in self.blobs.items():
this_color = colors[color_i % len(colors)]
color_i += 1
(x, y, w, h) = [int(v) for v in blob.bounding_box]
cv2.rectangle(frame, (x, y), (x + w, y + h), this_color, 2)
vehicle_label = 'I: ' + _id[:8] \
if blob.type is None \
else 'I: {0}, T: {1} ({2})'.format(_id[:8], blob.type, str(blob.type_confidence)[:4])
cv2.putText(frame, vehicle_label, (x, y - 5), font, 0.5,
this_color, 1, line_type)
# draw counting lines
for counting_line in self.counting_lines:
cv2.line(frame, counting_line['line'][0], counting_line['line'][1],
(255, 0, 0), 3)
cl_label_origin = (counting_line['line'][0][0],
counting_line['line'][0][1] + 35)
cv2.putText(frame, counting_line['label'], cl_label_origin, font,
1, (255, 0, 0), 2, line_type)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi)
# For each line, write the cumulative count on the video (note if you're detecting lots
# of different classes, this may overflow off the bottom of the video).
if self.draw_counts:
offset = 1
for line, objects in self.counts.items():
cv2.putText(frame, line, (10, 40 * offset), font, 1,
(255, 0, 0), 2, line_type)
offset += 1
for label, count in objects.items():
cv2.putText(frame, "{}: {}".format(label, count),
(10, 40 * offset), font, 1, (255, 0, 0), 2,
line_type)
offset += 1
return frame
def visualize(self):
frame = self.frame
font = cv2.FONT_HERSHEY_DUPLEX
line_type = cv2.LINE_AA
# draw and label blob bounding boxes
for _id, blob in self.blobs.items():
(x, y, w, h) = [int(v) for v in blob.bounding_box]
cv2.rectangle(frame, (x, y), (x + w, y + h), self.hud_color, 2)
object_label = 'I: ' + _id[:8] \
if blob.type is None \
else 'I: {0}, T: {1} ({2})'.format(_id[:8], blob.type, str(blob.type_confidence)[:4])
cv2.putText(frame, object_label, (x, y - 5), font, 1,
self.hud_color, 2, line_type)
# draw counting lines
for counting_line in self.counting_lines:
cv2.line(frame, counting_line['line'][0], counting_line['line'][1],
self.hud_color, 3)
cl_label_origin = (counting_line['line'][0][0],
counting_line['line'][0][1] + 35)
cv2.putText(frame, counting_line['label'], cl_label_origin, font,
1, self.hud_color, 2, line_type)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi)
# show counts
if self.show_counts:
offset = 1
for line, objects in self.counts.items():
cv2.putText(frame, line, (10, 40 * offset), font, 1,
self.hud_color, 2, line_type)
for label, count in objects.items():
offset += 1
cv2.putText(frame, "{}: {}".format(label, count),
(10, 40 * offset), font, 1, self.hud_color, 2,
line_type)
offset += 2
return frame
def visualize(self, roi_setting_mode, is_paused, showUI, veh_light,ped_light,light_time, roi_setting_mode_P,
line_setting_mode,line_setting_mode_P,vpoint_setting_mode,help_img_flag):
frame = self.frame
font = cv2. FONT_HERSHEY_COMPLEX
line_type = cv2.LINE_AA
occupys = []
offset = 0
lineDistance = distance_cal(self.counting_lines[0]['line'][0][1],self.camera_height,self.focal_length,self.pixel_length,self.resolution,self.vanishing_point)
text1 = 'fps: ' +str(round(self.processing_frame_rate,2))
text2 = 'Now have: ' +str(len(self.blobs))
cv2.putText(frame, str(time.asctime( time.localtime(time.time()))), (0 , self.f_height-10), font, 1, (255, 255, 0), 1, line_type)
get_text_box_with_background_color(frame,text1,(self.f_width - 300 , 50),font,1,(255, 255, 255),1,line_type,(0,0,0))
get_text_box_with_background_color(frame,text2,(self.f_width - 300 , 100),font,1,(255, 255, 255),1,line_type,(0,0,0))
# cv2.putText(frame, 'fps: ' +str(self.processing_frame_rate), (self.f_width - 150 , 50), font, 1, (25, 25, 25), 1, line_type)
# cv2.putText(frame, 'Now have: ' +str(len(self.blobs))+' objects', (self.f_width - 350 , 100), font, 1, (25, 25, 25), 1, line_type)
# draw and label blob bounding boxes
self.veh_light = veh_light
self.ped_light = ped_light
frame = get_traffic_light_image(frame, self.detector, veh_light, ped_light)
get_text_box_with_background_color(frame,str(light_time),(10 , 400),font,1,(255, 255, 255),1,line_type,(0,0,0))
for _id, blob in self.blobs.items():
(x, y, w, h) = [int(v) for v in blob.bounding_box]
if blob.isJaywalker == True:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 3)
else:
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 3)
for occupy in occupys:
if y >= occupy[0] and y <= occupy[1]:
offset+=1
if y-31 > occupy[0] and y-31 < occupy [1]:
offset+=1
# cv2.putText(frame, 'ID:' + str(_id), (x , y - 25), font, 0.7, (0, 0, 0), 2, line_type)
if self.detector == 'yolo':
distanceToLine = blob.distance - lineDistance
blob.distanceInLast3Frame.append(distanceToLine)
if len(blob.distanceInLast3Frame) > 3:
blob.distanceInLast3Frame.pop(0)
if len(blob.distanceInLast3Frame) == 3:
blob.mean_distanceInLast3Frame = list_equalization(blob.distanceBetween3Frames,abs(blob.distanceInLast3Frame[0] - blob.distanceInLast3Frame[2]),15)
blob.remainingTime = cal_remaining_time(round(distanceToLine-blob.mean_distanceInLast3Frame,1),2,self.processing_frame_rate)
if round(blob.remainingTime,1) > 0:
blob.speed = round(distanceToLine/blob.remainingTime,1)
get_text_box_with_background_color(frame,str(round(distanceToLine,1)) +'m '+ str(round(blob.remainingTime,1))+'s',(x , y - 5-(offset*35)),font,0.7,(0, 0, 0),2,line_type,(223,223,223))
if not self.veh_light == 0:
if blob.speed >= 1.5 and distanceToLine <= 40:
self.not_slowing_down_flag = True
else:
self.not_slowing_down_flag = False
else:
self.not_slowing_down_flag = False
# +str(round(distanceToLine/blob.remainingTime*3.6,1))+' km/h'
# cv2.putText(frame, str(round(distanceToLine,1)) +'m'+ str(round(blob.remainingTime,1))+'s', (x , y - 5), font, 0.7, (0, 0, 0), 2, line_type)
else:
if round(distanceToLine,1) > 0:
get_text_box_with_background_color(frame,str(round(distanceToLine,1)) +'m ',(x , y - 5-(offset*35)),font,0.7,(0, 0, 0),2,line_type,(223,223,223))
# cv2.putText(frame, str(round(distanceToLine,1)) +'m' , (x , y - 5), font, 0.7, (0, 0, 0), 2, line_type)
get_text_box_with_background_color(frame,'ID:' + str(_id),(x , y - 31 - (offset*35)),font,0.7,(0, 0, 0),2,line_type,(223,223,223))
cv2.line(frame, (x , y - 5-(offset*35)), (x,y), (255, 0, 0), 3)
occupys.append((y - 31 - (offset*35), y - (offset*35)))
else:
get_text_box_with_background_color(frame,'ID:' + str(_id),(x , y - 5),font,0.7,(0, 0, 0),2,line_type,(223,223,223))
if blob.isJaywalker:
get_text_box_with_background_color(frame,"Jaywalker detected.",(x , y - 30),font,0.7,(0, 0, 0),2,line_type,(223,223,223))
# draw counting lines
for counting_line in self.counting_lines:
cv2.line(frame, counting_line['line'][0], counting_line['line'][1], (255, 0, 0), 3)
# cl_label_origin = (counting_line['line'][0][0], counting_line['line'][0][1] + 35)
# cv2.putText(frame, str(round(self.blobDistance,1))+'m (' , cl_label_origin, font, 1, (255, 0, 0), 2, line_type)
# =============================================================================
# for road in self.roads:
# cv2.line(frame, road['line'][0], road['line'][1], (255, 0, 0), 3)
# r_label_origin = (road['line'][1][0] - 15 , road['line'][1][1] - 35)
# cv2.putText(frame, road['label'] , r_label_origin, font, 1, (255, 0, 0), 2, line_type)
# =============================================================================
# =============================================================================
# for speed_estimation_line in self.speed_estimation_lines:
# cv2.line(frame, speed_estimation_line['line'][0], speed_estimation_line['line'][1], (255, 0, 0), 3)
# sel_label_origin = (speed_estimation_line['line'][0][0], speed_estimation_line['line'][0][1] + 35)
# cv2.putText(frame, speed_estimation_line['label']+" speed", sel_label_origin, font, 1, (255, 0, 0), 2, line_type)
#
# =============================================================================
# =============================================================================
# if is_paused:
# cv2.putText(frame, 'Pausing', (round(self.f_width/2),30), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 0, 0), 1, cv2.LINE_AA)
# =============================================================================
if roi_setting_mode and self.detector == 'yolo':
get_text_box_with_background_color(frame,'Setting ROI.',(round(self.f_width/2)-150,30),font,1,(0, 0, 0),2,line_type,(255,255,255))
if roi_setting_mode_P and self.detector == 'yolo_p':
get_text_box_with_background_color(frame,'Setting ROI.',(round(self.f_width/2)-150,30),font,1,(0, 0, 0),2,line_type,(255,255,255))
if line_setting_mode and self.detector == 'yolo':
get_text_box_with_background_color(frame,'Setting Line.',(round(self.f_width/2)-150,30),font,1,(0, 0, 0),2,line_type,(255,255,255))
if line_setting_mode_P and self.detector == 'yolo_p':
get_text_box_with_background_color(frame,'Setting Line.',(round(self.f_width/2)-150,30),font,1,(0, 0, 0),2,line_type,(255,255,255))
if vpoint_setting_mode and self.detector == 'yolo':
get_text_box_with_background_color(frame,'Setting Vanishing Point.',(round(self.f_width/2)-150,30),font,1,(0, 0, 0),2,line_type,(255,255,255))
if help_img_flag and self.detector == 'yolo':
cv2.putText(frame, "Press 'h' to close user manual.", (self.f_width-750,self.f_height-30), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
if help_img_flag is False and self.detector == 'yolo':
cv2.putText(frame, "Press 'h' to open user manual", (self.f_width-750,self.f_height-30), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi,(255,255,0))
if self.detector == 'yolo_p':
frame = draw_roi(frame,self.waiting_zone[0:4],(0,255,255))
if len(self.waiting_zone)==8:
frame = draw_roi(frame,self.waiting_zone[-4:],(255,0,255))
if showUI:
if self.detector == 'yolo':
x,y = self.vanishing_point
cv2.line(frame, (x+50,y+50) , (x-50,y-50) , (0, 0, 0), 2)
cv2.line(frame, (x+50,y-50) , (x-50,y+50), (0, 0, 0), 2)
cv2.putText(frame, 'Showing Vanishing Point.', (round(self.f_width/2)-150,30), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 0, 0), 1, cv2.LINE_AA)
# =============================================================================
# for road in self.roads:
# cv2.line(frame, road['line'][0], road['line'][1], (255, 0, 0), 3)
# r_label_origin = (road['line'][1][0] - 15 , road['line'][1][1] - 35)
# cv2.putText(frame, road['label'] , r_label_origin, font, 1, (255, 0, 0), 2, line_type)
# =============================================================================
# show counts
if self.show_counts:
if self.detector == 'yolo':
offset = 1
for line, objects in self.counts.items():
cv2.putText(frame, line, (75, 40 * offset), font, 1, (255, 0, 0), 2, line_type)
for label, count in objects.items():
offset += 1
cv2.putText(frame, "{}: {}".format(label, count), (75, 40 * offset), font, 1, (255, 0, 0), 2, line_type)
offset += 2
if self.detector == 'yolo_p':
if self.veh_light == 0:
get_text_box_with_background_color(frame,"waiting zone have "+str(self.isWaiting)+" people.",(self.f_width - 550 , 150),font,1,(255, 255, 255),1,line_type,(0,0,0))
# adjust traffic light duration when vehicle traffic light is red and pedestrian traffic light is green.
if self.detector == 'yolo' and self.veh_light == 2 and self.ped_light == 1:
if len(self.blobs) == 0 and light_time < 6:
self.extend_flag = True
self.extend_notification = 10
print("2,1,process activated extend")
if self.detector == 'yolo_p' and self.veh_light == 2 and self.ped_light == 1:
if len(self.blobs) == 0 and light_time > 6:
self.reduce_flag = True
self.reduce_notification = 10
print("2,1,process activated reduce")
if self.extend_notification != 0 :
cv2.putText(frame, 'traffic light duration is extended', (10 , 450), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 0, 0), 1, cv2.LINE_AA)
self.extend_notification -= 0
if self.reduce_notification != 0 :
cv2.putText(frame, 'traffic light duration is reduced', (10 , 450), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 0, 0), 1, cv2.LINE_AA)
self.reduce_notification -= 0
# adjust traffic light duration when vehicle traffic light is green and pedestrian traffic light is red.
if self.detector == 'yolo' and self.veh_light == 0 and self.ped_light == 0:
# print(light_time)
# print(self.veh_light)
# print(self.ped_light)
if len(self.blobs) == 0 and light_time > 6:
self.reduce_flag = True
self.reduce_notification = 10
print("0,0,process activated reduce")
if self.detector == 'yolo_p' and self.veh_light == 0 and self.ped_light == 0:
if self.isWaiting == 0 and light_time < 6:
self.extend_flag = True
self.extend_notification = 10
print("0,0,process activated extend")
if self.extend_notification != 0 :
cv2.putText(frame, 'traffic light duration is extended', (10 , 450), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 0, 0), 1, cv2.LINE_AA)
self.extend_notification -= 1
if self.reduce_notification != 0 :
cv2.putText(frame, 'traffic light duration is reduced', (10 , 450), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 0, 0), 1, cv2.LINE_AA)
self.reduce_notification -= 1
if self.jaywalker_flag:
get_text_box_with_background_color(frame,"Warning: Jaywalker detected.",(250 , 100),font,2,(255, 255, 255),2,line_type,(0,0,255))
cv2.rectangle(frame, (0, 0), (self.f_width, self.f_height), (0, 0, 255), 10)
if self.not_slowing_down_flag:
get_text_box_with_background_color(frame,"Warning: High Speed Vehicle deteced.",(250 , 100),font,1,(255, 255, 255),2,line_type,(0,0,255))
cv2.rectangle(frame, (0, 0), (self.f_width, self.f_height), (0, 0, 255), 10)
return frame