forked from bingrao/vehicle-detection
/
visualizations.py
48 lines (33 loc) · 2.08 KB
/
visualizations.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
import cv2
import numpy as np
def draw_lane_status(frame, lane_info, threshold_offset = 0.6):
font = cv2.FONT_HERSHEY_SIMPLEX
info_road = "Lane Status"
info_lane = "Direction: {0}".format(lane_info['curve_direction'])
info_cur = "Curvature {:6.1f} m".format(lane_info['curvature'])
info_offset = "Off center: {0} {1:3.1f}m".format(lane_info['dev_dir'], lane_info['offset'])
l_uper = (10,10)
cv2.line(frame,(l_uper[0] + 265,0),(l_uper[0] + 265,155),(255,0,0),5)
cv2.putText(frame, info_road, (50,32+5), font, 0.8, (255,255,0), 2,cv2.LINE_AA)
cv2.putText(frame, info_lane, (16,60+10), font, 0.6, (255,255,0), 1,cv2.LINE_AA)
cv2.putText(frame, info_cur, (16,80+25), font, 0.6, (255,255,0), 1,cv2.LINE_AA)
if lane_info['offset'] >= threshold_offset:
cv2.putText(frame, info_offset, (16,100+40), font, 0.6, (255,0,0), 1,cv2.LINE_AA)
else:
cv2.putText(frame, info_offset, (16,100+40), font, 0.6, (255,255,0), 1,cv2.LINE_AA)
def draw_speed(img_cp, fps, w):
fps_info = "{0:4.1f} fps".format(fps)
cv2.putText(img_cp, 'Speed', (w - 120,37), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255,255,0), 2, cv2.LINE_AA)
cv2.putText(img_cp, fps_info, (w - 130,100), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255,255,0), 1, cv2.LINE_AA)
cv2.line(img_cp,(w-160,0),(w-160,155),(255,0,0),5)
def draw_thumbnails(img_cp, img, window_list, thumb_w=100, thumb_h=80, off_x=30, off_y=30):
cv2.putText(img_cp, 'Detected viehicles', (400,37), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255,255,0), 2, cv2.LINE_AA)
for i, bbox in enumerate(window_list):
thumbnail = img[bbox[0][1]:bbox[1][1], bbox[0][0]:bbox[1][0]]
vehicle_thumb = cv2.resize(thumbnail, dsize=(thumb_w, thumb_h))
start_x = 300 + (i+1) * off_x + i * thumb_w
img_cp[off_y + 30:off_y + thumb_h + 30, start_x:start_x + thumb_w, :] = vehicle_thumb
def draw_background_highlight(image, draw_img, w):
mask = cv2.rectangle(np.copy(image), (0, 0), (w, 155), (0, 0, 0), thickness=cv2.FILLED)
draw_img = cv2.addWeighted(src1=mask, alpha=0.3, src2=draw_img, beta=0.8, gamma=0)
return draw_img