class PreparingService(threading.Thread):
def __init__(self, sending_queue, stop_dict, cfg, ext_ratio=0.1):
super(PreparingService, self).__init__()
self.cfg = cfg
self.device_id = get_mac()
self.lp_detector = LicensePlateDetector(cfg.yolo_model)
self.segmentation = SegmentCharacter()
self.sending_queue = sending_queue
self.image_grabber = ImageGrabber(cfg.camera.url, cfg.camera.usb)
self.image_grabber.start()
self.ext_ratio = ext_ratio
self.stop_dict = stop_dict
def run(self):
while not self.stop_dict["PreparingService"]:
try:
if not self.image_grabber.stop:
image = self.image_grabber.get_frame()
bboxes, labels, conf_scores = self.lp_detector.detect(
image)
# Coordinate of characters in a license plate
char_coords = []
# Coordinate of license plate
coord_boxes = []
for i, bbox in enumerate(bboxes):
conf_score = conf_scores[i]
coord_box = [int(val) for val in bbox]
width = coord_box[2] - coord_box[0]
height = coord_box[3] - coord_box[1]
coord_box[0] = max(
0, int(coord_box[0] - width * self.ext_ratio))
coord_box[1] = max(
0, int(coord_box[1] - height * self.ext_ratio))
coord_box[2] = min(
image.shape[1],
int(coord_box[2] + width * self.ext_ratio))
coord_box[3] = min(
image.shape[0],
int(coord_box[3] + height * self.ext_ratio))
lp_image = image[coord_box[1]:coord_box[3],
coord_box[0]:coord_box[2]]
# print(lp_image.shape)
processing_time = time.time()
char_coord_perbox = self.segmentation.segment(lp_image)
# print("Processing time:", time.time() - processing_time)
if len(char_coord_perbox) > 0 and len(
char_coord_perbox) <= 10:
char_coord_perbox = pad_or_truncate(
char_coord_perbox, 10)
coord_boxes.append(coord_box)
char_coords.append(char_coord_perbox)
package = pickle.dumps({
"image": image,
"coord_boxes": coord_boxes,
"char_coords": char_coords,
"deviceID": self.device_id
})
self.sending_queue.put(package)
except Exception as e:
print(str(e))
self.image_grabber.stop = True
self.image_grabber.join()
borderValue=0.0)
return warped
if __name__ == "__main__":
import anyconfig
import munch
from image_grabber import ImageGrabber
import cv2
opt = anyconfig.load("settings.yaml")
opt = munch.munchify(opt)
detector = FaceDetector(opt.face_detector.model_path, -1)
imageGrabber = ImageGrabber(opt.camera.url, opt.camera.fps,
opt.camera.push2queue_freq, opt.camera.rgb)
imageGrabber.start()
fps = FPS().start()
while not imageGrabber.stop:
image = imageGrabber.get_frame()
bboxes, points = detector.detect(image, 1.0)
# Comment this stuff if you want to test FPS
aligned_faces = []
for i, bbox in enumerate(bboxes):
conf_score = bbox[4]
coords_box = [int(val) for val in bbox[:4]]
if conf_score < 0.5:
continue
x_min, y_min, x_max, y_max = coords_box
for point in points[i]:
cv2.circle(image, (point[0], point[1]), 1, (0, 255, 0), 3)
cv2.rectangle(image, (x_min, y_min), (x_max, y_max), (0, 255, 0),