# 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)