def main():
args = parse_args()
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/%s.trt) not found!' % args.model)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.category_num)
yolo_dim = args.model.split('-')[-1]
if 'x' in yolo_dim:
dim_split = yolo_dim.split('x')
if len(dim_split) != 2:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
w, h = int(dim_split[0]), int(dim_split[1])
else:
h = w = int(yolo_dim)
if h % 32 != 0 or w % 32 != 0:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num)
open_window(WINDOW_NAME, 'Camera TensorRT YOLO Demo', 640, 480)
vis = BBoxVisualization(cls_dict)
loop_and_detect(cam, trt_yolo, conf_th=0.3, vis=vis)
cam.release()
cv2.destroyAllWindows()
def main():
args = parse_args()
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/%s.trt) not found!' % args.model)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.category_num)
vis = BBoxVisualization(cls_dict)
h, w = get_input_shape(args.model)
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num, args.letter_box)
open_window(WINDOW_NAME, 'Camera TensorRT YOLO Demo', cam.img_width,
cam.img_height)
msg_queue = Queue(maxsize=100)
# msg_queue.put("0,0,0,-1".encode())
Thread(target=serArd, args=(msg_queue, )).start()
loop_and_detect(cam, trt_yolo, msg_queue, conf_th=0.7, vis=vis)
while True:
pass
cam.release()
cv2.destroyAllWindows()
def main():
print(f"{datetime.datetime.now().isoformat()} start!", flush=True)
args = parse_args()
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/%s.trt) not found!' % args.model)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.category_num)
yolo_dim = args.model.split('-')[-1]
if 'x' in yolo_dim:
dim_split = yolo_dim.split('x')
if len(dim_split) != 2:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
w, h = int(dim_split[0]), int(dim_split[1])
else:
h = w = int(yolo_dim)
if h % 32 != 0 or w % 32 != 0:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num)
# open_window(
# WINDOW_NAME, 'Camera TensorRT YOLO Demo',
# cam.img_width, cam.img_height)
vis = BBoxVisualization(cls_dict)
loop_and_detect(cam, trt_yolo, conf_th=0.3, vis=vis)
cam.release()
def main():
args = parse_args()
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/%s.trt) not found!' % args.model)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.category_num)
vis = BBoxVisualization(cls_dict)
h, w = get_input_shape(args.model)
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num, args.letter_box)
mjpeg_server = MjpegServer(port=args.mjpeg_port)
print('MJPEG server started...')
try:
loop_and_detect(cam,
trt_yolo,
conf_th=0.3,
vis=vis,
mjpeg_server=mjpeg_server)
except Exception as e:
print(e)
finally:
mjpeg_server.shutdown()
cam.release()
def yolo_detection():
# dev = cuda.Device(0)
# ctx = dev.make_context()
args = parse_args()
print(args)
"""
config assert
"""
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/darknet/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/darknet/%s.trt) not found!' %
args.model)
cls_dict = get_cls_dict(args.category_num)
yolo_dim = args.model.split('-')[-1]
if 'x' in yolo_dim:
dim_split = yolo_dim.split('x')
if len(dim_split) != 2:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
w, h = int(dim_split[0]), int(dim_split[1])
else:
h = w = int(yolo_dim)
if h % 32 != 0 or w % 32 != 0:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
"""
capture the image
"""
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
"""
deploy the yolo model
"""
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num)
# open_window(
# WINDOW_NAME, 'Camera TensorRT YOLO Demo',
# cam.img_width, cam.img_height)
"""
detect the insulator using model
"""
vis = BBoxVisualization(cls_dict)
loop_and_detect(cam, trt_yolo, conf_th=0.3, vis=vis)
"""
release the image
"""
cam.release()
def main():
args = parse_args()
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
mtcnn = TrtMtcnn()
open_window(
WINDOW_NAME, 'Camera TensorRT MTCNN Demo for Jetson Nano',
cam.img_width, cam.img_height)
loop_and_detect(cam, mtcnn, args.minsize)
cam.release()
cv2.destroyAllWindows()
def main():
# Parse arguments and get input
args = parse_args()
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
# Create NN1 and NN2 models and load into memory
cls_dict = get_cls_dict(args.model.split('_')[-1])
trt_ssd = TrtSSD(args.model, INPUT_HW)
mtcnn = TrtMtcnn()
# Create Preview Window
open_window(WINDOW_NAME, 'Camera Preview', cam.img_width, cam.img_height)
vis = BBoxVisualization(cls_dict)
# Enter Detection Mode
while True:
# Get Image
img = cam.read()
out.write(img)
nn1_results = []
# Run Neural Networks
img, nn1_results, nn2_results, nn3_results = loop_and_detect(
img, mtcnn, args.minsize, trt_ssd, conf_th=0.3, vis=vis)
# Communicate to Arduino
if (nn1_results != []):
img = robot_drive(img, nn1_results)
else:
serial_port.write("N".encode())
print("N")
# Display and save output
cv2.imshow(WINDOW_NAME, img)
outNN.write(img)
# User/Keyboard Input
key = cv2.waitKey(1)
if key == ord('q'):
out.release()
outNN.release()
break
# Clean up and exit
cam.release()
cv2.destroyAllWindows()
serial_port.close()
def main():
args = parse_args()
labels = np.loadtxt('googlenet/synset_words.txt', str, delimiter='\t')
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
# initialize the tensorrt googlenet engine
net = PyTrtGooglenet(DEPLOY_ENGINE, ENGINE_SHAPE0, ENGINE_SHAPE1)
open_window(WINDOW_NAME, 'Camera TensorRT GoogLeNet Demo', cam.img_width,
cam.img_height)
loop_and_classify(cam, net, labels, args.crop_center)
cam.release()
cv2.destroyAllWindows()
def main():
args = parse_args()
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.model.split('_')[-1])
trt_ssd = TrtSSD(args.model, INPUT_HW)
open_window(WINDOW_NAME, 'Camera TensorRT SSD Demo', cam.img_width,
cam.img_height)
vis = BBoxVisualization(cls_dict)
loop_and_detect(cam, trt_ssd, conf_th=0.3, vis=vis)
cam.release()
cv2.destroyAllWindows()
def main():
args = parse_args()
labels = np.loadtxt('googlenet/synset_words.txt', str, delimiter='\t')
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
open_window(WINDOW_NAME, 'Camera TensorRT GoogLeNet Demo', cam.img_width,
cam.img_height)
condition = threading.Condition()
trt_thread = TrtGooglenetThread(condition, cam, labels, args.crop_center)
trt_thread.start() # start the child thread
loop_and_display(condition)
trt_thread.stop() # stop the child thread
cam.release()
cv2.destroyAllWindows()
def main():
args = parse_args()
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/%s.trt) not found!' % args.model)
client = init_mqtt(args.host, args.port)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.category_num)
print("cls_dict:", cls_dict)
#print(cls_dict[3])
yolo_dim = args.model.split('-')[-1]
print("yolo_dim:", yolo_dim)
if 'x' in yolo_dim:
dim_split = yolo_dim.split('x')
if len(dim_split) != 2:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
w, h = int(dim_split[0]), int(dim_split[1])
else:
h = w = int(yolo_dim)
print('w:{0}, h:{1}'.format(w, h))
if h % 32 != 0 or w % 32 != 0:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num, args.letter_box)
open_window(WINDOW_NAME, 'Camera TensorRT YOLO Demo', cam.img_width,
cam.img_height)
vis = BBoxVisualization(cls_dict)
loop_and_detect(cam, trt_yolo, conf_th=0.3, vis=vis, \
cls_dict=cls_dict, client=client, topic=args.topic)
cam.release()
cv2.destroyAllWindows()
client.disclose()
def main():
args = parse_args()
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cuda.init() # init pycuda driver
cls_dict = get_cls_dict(args.model.split('_')[-1])
open_window(WINDOW_NAME, 'Camera TensorRT SSD Demo', cam.img_width,
cam.img_height)
vis = BBoxVisualization(cls_dict)
condition = threading.Condition()
trt_thread = TrtThread(condition, cam, args.model, conf_th=0.3)
trt_thread.start() # start the child thread
loop_and_display(condition, vis)
trt_thread.stop() # stop the child thread
cam.release()
cv2.destroyAllWindows()
def main():
args = parse_args()
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/%s.trt) not found!' % args.model)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.category_num)
vis = BBoxVisualization(cls_dict)
trt_yolo = TrtYOLO(args.model, args.category_num, args.letter_box)
open_window(WINDOW_NAME, 'Camera TensorRT YOLO Demo', cam.img_width,
cam.img_height)
loop_and_detect(cam, trt_yolo, conf_th=0.3, vis=vis)
cam.release()
cv2.destroyAllWindows()
def main():
args = parse_args()
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/%s.trt) not found!' % args.model)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.category_num)
yolo_dim = args.model.split('-')[-1]
if 'x' in yolo_dim:
dim_split = yolo_dim.split('x')
if len(dim_split) != 2:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
w, h = int(dim_split[0]), int(dim_split[1])
else:
h = w = int(yolo_dim)
if h % 32 != 0 or w % 32 != 0:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num)
vis = BBoxVisualization(cls_dict)
mjpeg_server = MjpegServer(port=args.mjpeg_port)
print('MJPEG server started...')
try:
loop_and_detect(cam,
trt_yolo,
conf_th=0.3,
vis=vis,
mjpeg_server=mjpeg_server)
except Exception as e:
print(e)
finally:
mjpeg_server.shutdown()
cam.release()
def main():
args = parse_args()
if not os.path.isfile('retinaface/%s.trt' % args.model):
raise SystemExit('ERROR: file (retinaface/%s.trt) not found!' % args.model)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cfg = cfg_mnet
input_size = args.model.split('-')[-1]
input_shape = (int(input_size), int(input_size))
priorbox = PriorBox(cfg, input_shape)
priors = priorbox.forward()
trt_retinaface = TRT_RetinaFace(args.model, input_shape)
open_window(
WINDOW_NAME, 'Camera TensorRT Face Detection Demo',
cam.img_width, cam.img_height)
loop_and_detect(cam, trt_retinaface, priors, cfg)
cam.release()
cv2.destroyAllWindows()
def main():
args = parse_args()
if args.category_num <= 0:
raise SystemExit('ERROR: bad category_num (%d)!' % args.category_num)
if not os.path.isfile('yolo/%s.trt' % args.model):
raise SystemExit('ERROR: file (yolo/%s.trt) not found!' % args.model)
cam = Camera(args)
if not cam.isOpened():
raise SystemExit('ERROR: failed to open camera!')
cls_dict = get_cls_dict(args.category_num)
yolo_dim = args.model.split('-')[-1]
if 'x' in yolo_dim:
dim_split = yolo_dim.split('x')
if len(dim_split) != 2:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
w, h = int(dim_split[0]), int(dim_split[1])
else:
h = w = int(yolo_dim)
if h % 32 != 0 or w % 32 != 0:
raise SystemExit('ERROR: bad yolo_dim (%s)!' % yolo_dim)
load_weight_start = time.time()
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num)
load_weights_time = datetime.timedelta(seconds=time.time() -
load_weight_start)
print('Load weights Time: %s' % (load_weights_time))
open_window(WINDOW_NAME, 'Camera TensorRT YOLO Demo', cam.img_width,
cam.img_height)
vis = BBoxVisualization(cls_dict)
loop_and_detect(cam, trt_yolo, conf_th=0.3, vis=vis)
reporter = MemReporter()
reporter.report()
cam.release()
cv2.destroyAllWindows()
