def main():
args = parse_args()
if args.category_num <= 0:
raise SystemExit(f'ERROR: bad category_num ({args.category_num})!')
if not os.path.isfile(args.model):
raise SystemExit(f'ERROR: file {args.model} not found!')
# Process valid coco json file
process_valid_json(args.valid_coco)
if args.write_images:
if not os.path.exists(args.image_output): os.mkdir(args.image_output)
# Create camera for video/image input
cam = Camera(args)
if not cam.get_is_opened():
raise SystemExit('ERROR: failed to open camera!')
class_dict = get_cls_dict(args.category_num)
yolo_dim = (args.model.replace(".trt", "")).split('-')[-1]
if 'x' in yolo_dim:
dim_split = yolo_dim.split('x')
if len(dim_split) != 2:
raise SystemExit(f'ERROR: bad yolo_dim ({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(f'ERROR: bad yolo_dim ({yolo_dim})!')
# Create yolo
trt_yolo = TrtYOLO(args.model, (h, w), args.category_num)
if args.activate_display:
open_window(WINDOW_NAME, 'Camera TensorRT YOLO Demo', cam.img_width,
cam.img_height)
visual = BBoxVisualization(class_dict)
# Run detection
loop_and_detect(cam,
trt_yolo,
args,
confidence_thresh=args.confidence_threshold,
visual=visual)
# Clean up
cam.release()
if args.activate_display:
cv2.destroyAllWindows()
def main():
args = parse_args()
cam = Camera(args)
if not cam.get_is_opened():
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():
args = parse_args()
labels = np.loadtxt('googlenet/synset_words.txt', str, delimiter='\t')
cam = Camera(args)
if not cam.get_is_opened():
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.get_is_opened():
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.get_is_opened():
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()
cam = Camera(args)
if not cam.get_is_opened():
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()
