parser.add_argument('--filename',
default='filename',
help='filename to read data from')
parser.add_argument('--month', type=int)
args = parser.parse_args()
args.cfg = check_file(args.cfg) # check file
args.names = check_file(args.names) # check file
file_to_read = args.filename
print("Yolo for vehicle detection configuration:")
print(args)
directory_exists = os.path.isdir(args.save_path)
if not directory_exists:
os.mkdir(args.save_path)
i = database_iterator()
print(f"total network cameras: {i.numcams}")
vehicle_detector = Vehicle_Detector(weights=args.weights,
cfg=args.cfg,
names=args.names,
iou_thres=args.iou_thres,
conf_thres=args.conf_thres,
imgsz=args.img_size,
half=args.half,
device_id=args.device)
detections = dict()
day_night = dict()
count = 0
text_file = open(file_to_read, 'r')
def main(person_model, vehicle_detector, subset_all_images, process_num):
i = database_iterator()
person_detections = dict()
day_night = dict()
vehicle_detections = dict()
vehicle_filename = os.path.join(
args.save_path, "vehicle_detections_" + str(process_num) + ".json")
person_filename = os.path.join(
args.save_path, "person_detections_" + str(process_num) + ".json")
day_night_filename = os.path.join(
args.save_path, "day_night_" + str(process_num) + ".json")
for foldername, image_link, time in i.get_subset_images(
cam_list=subset_all_images):
print(foldername)
person_detections[foldername] = dict()
day_night[foldername] = dict()
check = all_same(i, image_link)
if len(image_link) > 0 and not check:
for j in range(len(image_link)):
print(j)
pil_image = (i.get_image(image_link[j]))
img = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
# day night calculation
if determine_day_night(img) == 0:
day_night[foldername][image_link[j]] = 'night'
else:
day_night[foldername][image_link[j]] = 'day'
# person detection
results = inference_detector(person_model, img)
if isinstance(results, tuple):
bbox_result, segm_result = results
else:
bbox_result, segm_result = results, None
bboxes = np.vstack(bbox_result)
bboxes = bboxes.tolist()
bbox_dict = dict()
for each in bboxes:
bbox_dict[each[4]] = each[0:4]
person_detections[foldername][image_link[j]] = bbox_dict
"""
# vehicle detection
img = np.array(pil_image.convert('RGB'))
results = vehicle_detector.detect(img, view_img=False)
vehicle_detections[foldername][image_link[j]] = results
# if j % 20 == 19:
# print(f"{j + 1} done out of {len(image_link)} images")
"""
# write to the file at the end of every camera instead of when the entire process is complete
# Helps if it gets disconnected in between
"""
f = open(vehicle_filename, "w+")
f.write(json.dumps(vehicle_detections))
f.close()
"""
f = open(person_filename, "w+")
f.write(json.dumps(person_detections))
f.close()
f = open(day_night_filename, "w+")
f.write(json.dumps(day_night))
f.close()