def detect_lp(output_dir, loaded_models, Iorig_name):
imgs_paths = glob('%s/%s_*car.png' % (output_dir, Iorig_name))
print('Searching for license plates...')
for i, img_path in enumerate(imgs_paths):
bname = splitext(basename(img_path))[0]
lp_net, lp_meta, lp_threshold = loaded_models[1]
R, _ = detect(lp_net,
lp_meta,
img_path.encode('utf-8'),
thresh=lp_threshold)
if len(R):
Iorig = cv2.imread(img_path)
WH = np.array(Iorig.shape[1::-1], dtype=float)
Llp = []
for i, r in enumerate(R):
cx, cy, w, h = (np.array(r[2]) / np.concatenate(
(WH, WH))).tolist()
tl = np.array([cx - w / 2., cy - h / 2.])
br = np.array([cx + w / 2., cy + h / 2.])
label = Label(0, tl, br)
Ilp = crop_region(Iorig, label)
Llp.append(label)
cv2.imwrite('%s/%s_lp.png' % (output_dir, bname), Ilp)
lwrite('%s/%s_lp.txt' % (output_dir, bname), Llp)
else:
print('No license plate found')
def detect_vehicle(img_path, output_dir, loaded_models, bname):
vehicle_net, vehicle_meta, vehicle_threshold = loaded_models[0]
R, _ = detect(vehicle_net,
vehicle_meta,
img_path.encode('utf-8'),
thresh=vehicle_threshold)
R = [r for r in R if r[0].decode(encoding='utf-8') in ['car']]
print('%d cars found' % len(R))
if len(R):
Iorig = cv2.imread(img_path)
WH = np.array(Iorig.shape[1::-1], dtype=float)
Lcars = []
for i, r in enumerate(R):
cx, cy, w, h = (np.array(r[2]) / np.concatenate((WH, WH))).tolist()
tl = np.array([cx - w / 2., cy - h / 2.])
br = np.array([cx + w / 2., cy + h / 2.])
label = Label(0, tl, br)
Icar = crop_region(Iorig, label)
Lcars.append(label)
cv2.imwrite('%s/%s_%dcar.png' % (output_dir, bname, i), Icar)
lwrite('%s/%s_cars.txt' % (output_dir, bname), Lcars)
def find_vehicle_one_img(img_path, veh_net, veh_meta, out_dir, veh_thd):
st = time.time()
print '\tScanning %s' % img_path
bname = basename(splitext(img_path)[0])
R, _ = dn.detect(veh_net, veh_meta, img_path, thresh=veh_thd)
# R: [name, prob, [x center, y center, width, height]]
R = [r for r in R if r[0] in ['car', 'bus']]
out_img = []
out_label_f = ""
if len(R):
Iorig = cv2.imread(img_path)
WH = np.array(Iorig.shape[1::-1], dtype=float)
Lcars = []
for i, r in enumerate(R):
cx, cy, w, h = (np.array(r[2]) / np.concatenate((WH, WH))).tolist()
tl = np.array([cx - w / 2., cy - h / 2.])
br = np.array([cx + w / 2., cy + h / 2.])
label = Label(0, tl, br)
Icar = crop_region(Iorig, label)
Lcars.append(label)
p_img = '%s/%s_%dcar.png' % (out_dir, bname, i)
cv2.imwrite(p_img, Icar)
out_img.append(p_img)
out_label_f = '%s/%s_cars.txt' % (out_dir, bname)
lwrite(out_label_f, Lcars)
print '\t\t%d cars found, runtime: %.1fs' % (len(R), time.time() - st)
return out_img, out_label_f
def vehicle_detection(img_path, output_dir):
try:
if not isdir(output_dir):
makedirs(output_dir)
bname = basename(splitext(img_path)[0])
plates = []
# Vehicle detection
R, _ = detect(vehicle_net,
vehicle_meta,
img_path,
thresh=vehicle_threshold)
R = [r for r in R if r[0] in ['car', 'bus', 'motorbike']]
# print '\t\t%d cars found' % len(R)
if not len(R):
return ("", plates)
Iorig = cv2.imread(img_path)
WH = np.array(Iorig.shape[1::-1], dtype=float)
Lcars = []
for i, r in enumerate(R):
cx, cy, w, h = (np.array(r[2]) / np.concatenate((WH, WH))).tolist()
tl = np.array([cx - w / 2., cy - h / 2.])
br = np.array([cx + w / 2., cy + h / 2.])
label = Label(0, tl, br)
Icar = crop_region(Iorig, label)
Lcars.append(label)
carImagePath = '%s/%s_%dcar.png' % (output_dir, bname, i)
cv2.imwrite(carImagePath, Icar)
#print("CarImagePath: ", carImagePath)
# LP detection
LPImagePath = LPDection(carImagePath)
if LPImagePath:
lp_str = OCRDection(LPImagePath)
if lp_str:
plates.append(lp_str)
lwrite('%s/%s_cars.txt' % (output_dir, bname), Lcars)
# draw yellow box around the cars and red box around license plates
genOutput(img_path, output_dir, bname)
return ('%s/%s_output.png' % (output_dir, bname), plates)
except:
traceback.print_exc()
return ("", plates)
def detect_vehicle(self, img, filename):
data = []
copy = img
R, boxes, confidences, class_ids = self.vehicle.detect_objects(copy, str(filename).split('.')[0] + '.txt')
if len(R):
WH = np.array(copy.shape[1::-1], dtype=float)
Lcars = []
for i, r in enumerate(R):
cx, cy, w, h = (np.array(boxes[i])/np.concatenate((WH, WH))).tolist()
tl = np.array([cx - w/2., cy - h/2.])
br = np.array([cx + w/2., cy + h/2.])
label = Label(0, tl, br)
Lcars.append(label)
data.append((cx, cy, w, h))
cv2.imwrite('%s/%s-car.png' % (self.output_dir, filename), copy)
lwrite('%s/%s-car.txt' % (self.output_dir, filename), Lcars)
return data
print('\t\t%d cars found' % len(R))
if len(R):
Iorig = cv2.imread(img_path)
WH = np.array(Iorig.shape[1::-1], dtype=float)
Lcars = []
for i, r in enumerate(R):
cx, cy, w, h = (np.array(r[2]) / np.concatenate(
(WH, WH))).tolist()
tl = np.array([cx - w / 2., cy - h / 2.])
br = np.array([cx + w / 2., cy + h / 2.])
label = Label(0, tl, br)
Icar = crop_region(Iorig, label)
Lcars.append(label)
cv2.imwrite('%s/%s_%dcar.png' % (output_dir, bname, i),
Icar)
lwrite('%s/%s_cars.txt' % (output_dir, bname), Lcars)
except:
traceback.print_exc()
sys.exit(1)
sys.exit(0)
Iorig = cv2.imread(img_path)
WH = np.array(Iorig.shape[1::-1], dtype=float)
Lcars = []
for i, r in enumerate(R):
cx, cy, w, h = (np.array(r[2]) / np.concatenate(
(WH, WH))).tolist()
tl = np.array([cx - w / 2., cy - h / 2.])
br = np.array([cx + w / 2., cy + h / 2.])
label = Label(0, tl, br, category=r[0].decode("utf-8"))
Icar = crop_region(Iorig, label)
Lcars.append(label)
cv2.imwrite(
# '%s/%s_%dcar.png' % (output_dir, bname, i), Icar)
'%s/%s_car_%d.png' % (output_dir, bname, i),
Icar)
lwrite('%s/%s_cars.txt' % (output_dir, bname),
Lcars,
write_category_names=True)
except:
traceback.print_exc()
sys.exit(1)
sys.exit(0)
R, _ = detect(lp_net,
lp_meta,
img_path.encode('utf-8'),
thresh=lp_threshold)
#R = [r for r in R if r[0] in ['lp']]
if len(R):
Iorig = cv2.imread(img_path)
WH = np.array(Iorig.shape[1::-1], dtype=float)
Llp = []
for i, r in enumerate(R):
cx, cy, w, h = (np.array(r[2]) / np.concatenate(
(WH, WH))).tolist()
tl = np.array([cx - w / 2., cy - h / 2.])
br = np.array([cx + w / 2., cy + h / 2.])
label = Label(0, tl, br)
Ilp = crop_region(Iorig, label)
Llp.append(label)
cv2.imwrite('%s/%s_lp.png' % (output_dir, bname), Ilp)
lwrite('%s/%s_lp.txt' % (output_dir, bname), Llp)
except:
traceback.print_exc()
sys.exit(1)
sys.exit(0)
