def save_predict(output,
gt,
img_name,
dataset,
save_path,
output_grey=False,
output_color=True,
gt_color=False):
if output_grey:
output_grey = Image.fromarray(output)
output_grey.save(os.path.join(save_path, img_name + '.png'))
if output_color:
if dataset == 'cityscapes':
output_color = cityscapes_colorize_mask(output)
elif dataset == 'camvid':
output_color = camvid_colorize_mask(output)
output_color.save(os.path.join(save_path, img_name + '_color.png'))
if gt_color:
if dataset == 'cityscapes':
gt_color = cityscapes_colorize_mask(gt)
elif dataset == 'camvid':
gt_color = camvid_colorize_mask(gt)
gt_color.save(os.path.join(save_path, img_name + '_gt.png'))
def save_predict(output,
gt,
img_name,
dataset,
save_path,
output_grey=False,
output_color=True,
gt_color=False):
if output_grey:
row, col = output.shape
dst = np.ones((row, col), dtype=np.uint8) * 255
for i in range(19):
dst[output == i] = color_list[i]
output_grey = Image.fromarray(dst)
output_grey.save(os.path.join(save_path, img_name[:-1] + '.png'))
if output_color:
if dataset == 'cityscapes':
output_color = cityscapes_colorize_mask(output)
elif dataset == 'camvid':
output_color = camvid_colorize_mask(output)
output_color.save(os.path.join(save_path,
img_name[:-1] + '_color.png'))
if gt_color:
if dataset == 'cityscapes':
gt_color = cityscapes_colorize_mask(gt)
elif dataset == 'camvid':
gt_color = camvid_colorize_mask(gt)
gt_color.save(os.path.join(save_path, img_name + '_gt.png'))