def compute_one(img_path,gt_path):
out = img_path
gt = load_image(gt_path)
# val_gt_erode paired with [0,0,0]label value
# label order: R G B
# num_classes = len(label_values)
gt = util.reverse_one_hot(util.one_hot_it(gt, label_values))
output_image = util.reverse_one_hot(util.one_hot_it(out, label_values))
running_metrics_val.update(gt, output_image)
def compute_one(img_path, gt_path):
gt = load_image(gt_path)
# val_gt_erode paired with [0,0,0]label value
# label order: R G B
# num_classes = len(label_values)
gt = util.reverse_one_hot(util.one_hot_it(gt, label_values))
gt_binary = np.zeros(gt.shape, dtype=np.uint8)
gt_binary[gt == object_class] = 1
output_image = img_path
running_metrics_val.update(gt_binary, output_image)