简介
简介参考:PASCAL VOC and SBD (the augment dataset) 总结
地址:http://home.bharathh.info/pubs/codes/SBD/download.html
下载下来的的数据集有cls img inst三个文件夹。
cls：语义标签，但是是.mat格式img：文件夹则是样本
1. mat转语义png
这里直接上code。 只需要修改main函数中的input_path output_path就ok了
from __future__ import print_functionimport osimport sysimport globimport scipy.iofrom PIL import Image as PILImage# Mat to png conversion for http://www.cs.berkeley.edu/~bharath2/codes/SBD/download.html# 'GTcls' key is for class segmentation# 'GTinst' key is for instance segmentationdef mat2png_hariharan(mat_file, key='GTcls'):mat = scipy.io.loadmat(mat_file, mat_dtype=True, squeeze_me=True, struct_as_record=False)return mat[key].Segmentationdef main():# input_path, output_path = process_arguments("/home/data/CM/data/Segmentation/voc12_aug/benchmark_RELEASE/dataset/cls")input_path = "./voc12_aug/benchmark_RELEASE/dataset/cls"# mat所在文件夹output_path = './voc12_aug/benchmark_RELEASE/dataset/seg'# 输出的语义png存放文件夹if os.path.isdir(input_path) and os.path.isdir(output_path):mat_files = glob.glob(os.path.join(input_path, '*.mat'))convert_mat2png(mat_files, output_path)else:help('Input or output path does not exist!\n')def process_arguments(argv):num_args = len(argv)input_path = Noneoutput_path = Noneif num_args == 3:input_path = argv[1]output_path = argv[2]else:help()return input_path, output_pathdef convert_mat2png(mat_files, output_path):if not mat_files:help('Input directory does not contain any Matlab files!\n')for mat in mat_files:numpy_img = mat2png_hariharan(mat)pil_img = PILImage.fromarray(numpy_img)pil_img.save(os.path.join(output_path, modify_image_name(mat, 'png')))# Extract name of image from given path, replace its extension with specified one# and return new name only, not path.def modify_image_name(path, ext):return os.path.basename(path).split('.')[0] + '.' + extdef help(msg=''):print(msg +'Usage: python mat2png.py INPUT_PATH OUTPUT_PATH\n''INPUT_PATH denotes path containing Matlab files for conversion.\n''OUTPUT_PATH denotes path where converted Png files ar going to be saved.', file=sys.stderr)exit()if __name__ == '__main__':main()
2. 语义图可视化
语义图的差别是很小的。这里再给出一个可视化脚本，将类别进行颜色可视化。
code
from __future__ import print_functionimport osimport sysimport numpy as npfrom skimage.io import imread, imsaveimport globdef pascal_palette():palette = {(0, 0, 0): 0,(128, 0, 0): 1,(0, 128, 0): 2,(128, 128, 0): 3,(0, 0, 128): 4,(128, 0, 128): 5,(0, 128, 128): 6,(128, 128, 128): 7,(64, 0, 0): 8,(192, 0, 0): 9,(64, 128, 0): 10,(192, 128, 0): 11,(64, 0, 128): 12,(192, 0, 128): 13,(64, 128, 128): 14,(192, 128, 128): 15,(0, 64, 0): 16,(128, 64, 0): 17,(0, 192, 0): 18,(128, 192, 0): 19,(0, 64, 128): 20}return palettedef convert_from_color_segmentation(seg):color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8)palette = pascal_palette()for c, i in palette.items():color_seg[ seg == i] = ccolor_seg = color_seg[..., ::-1]return color_segdef main():##ext = '.png'### path, txt_file, path_converted = process_arguments(sys.argv)path = './voc12_aug/benchmark_RELEASE/dataset/seg/*.png'# 前面转换后的语义图片path_converted = './voc12_aug/benchmark_RELEASE/dataset/seg_visualize'# 着色后的图片的保存位置# Create dir for converted labelsif not os.path.isdir(path_converted):os.makedirs(path_converted)f = glob.glob(path)for img_name in f:img_base_name = os.path.basename(img_name)img = imread(img_name)if (len(img.shape) == 2):img = convert_from_color_segmentation(img)imsave(os.path.join(path_converted, img_base_name), img)else:print(img_name + " is not composed of three dimensions, therefore ""shouldn't be processed by this script.\n""Exiting.", file=sys.stderr)exit()def process_arguments(argv):if len(argv) != 4:help()path = argv[1]list_file = argv[2]new_path = argv[3]return path, list_file, new_pathdef help():print('Usage: python convert_labels.py PATH LIST_FILE NEW_PATH\n''PATH points to directory with segmentation image labels.\n''LIST_FILE denotes text file containing names of images in PATH.\n''Names do not include extension of images.\n''NEW_PATH points to directory where converted labels will be stored.', file=sys.stderr)exit()if __name__ == '__main__':main()
结果
