# parser.add_argument('-t', '--template_images_dir', default='/home/mayank_sati/Desktop/qatm_data/template/')
parser.add_argument('-t',
'--template_images_dir',
default='data/cust_template_2')
# parser.add_argument('-t', '--template_images_dir', default='sample')
# parser.add_argument('-t', '--template_images_dir', default='data/cust_template/')
parser.add_argument('--alpha', type=float, default=25)
parser.add_argument('--thresh_csv',
type=str,
default='thresh_template.csv')
args = parser.parse_args()
template_dir = args.template_images_dir
image_path = args.sample_image
dataset = ImageDataset(Path(template_dir),
image_path,
thresh_csv='thresh_template.csv')
print("define model...")
model = CreateModel(model=models.vgg19(pretrained=True).features,
alpha=args.alpha,
use_cuda=args.cuda)
print("calculate score...")
# scores, w_array, h_array, thresh_list = run_multi_sample(model, dataset)
scores, w_array, h_array, thresh_list = run_one_sample_mayank(
model, dataset)
print("nms...")
# boxes, indices = nms_multi(scores, w_array, h_array, thresh_list)
thresh_list = 0.8
boxes = nms(scores, w_array, h_array, thresh_list)
# _ = plot_result_multi(dataset.image_raw, boxes, indices, show=True, save_name='result.png')
# parser.add_argument('-t', '--template_images_dir', default='sample')
# parser.add_argument('-t', '--template_images_dir', default='data/cust_template/')
parser.add_argument('--alpha', type=float, default=25)
parser.add_argument(
'--thresh_csv',
type=str,
default=
'/home/mayank_s/playing_ros/c++/ros2_play_old/src/oneshot/oneshot/thresh_template.csv'
)
args = parser.parse_args()
template_dir = args.template_images_dir
image_path = args.sample_image
dataset = ImageDataset(
Path(template_dir),
image_path,
thresh_csv=
'/home/mayank_s/playing_ros/c++/ros2_play_old/src/oneshot/oneshot/thresh_template.csv'
)
print("define model...")
model = CreateModel(model=models.vgg19(pretrained=True).features,
alpha=args.alpha,
use_cuda=args.cuda)
print("calculate score...")
# scores, w_array, h_array, thresh_list = run_multi_sample(model, dataset)
scores, w_array, h_array, thresh_list = run_one_sample_mayank(
model, dataset)
print("nms...")
# boxes, indices = nms_multi(scores, w_array, h_array, thresh_list)
thresh_list = 0.9
boxes = nms(scores, w_array, h_array, thresh_list)