[Feature] Add results2img, format_results for ade dataset (#544)

* [Feature] Add results2img, format_results for ade dataset.

* clean rebundant code.
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sennnnn 2021-05-17 10:29:28 +08:00 committed by GitHub
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@ -1,3 +1,10 @@
import os.path as osp
import tempfile
import mmcv
import numpy as np
from PIL import Image
from .builder import DATASETS
from .custom import CustomDataset
@ -82,3 +89,75 @@ class ADE20KDataset(CustomDataset):
seg_map_suffix='.png',
reduce_zero_label=True,
**kwargs)
def results2img(self, results, imgfile_prefix, to_label_id):
"""Write the segmentation results to images.
Args:
results (list[list | tuple | ndarray]): Testing results of the
dataset.
imgfile_prefix (str): The filename prefix of the png files.
If the prefix is "somepath/xxx",
the png files will be named "somepath/xxx.png".
to_label_id (bool): whether convert output to label_id for
submission
Returns:
list[str: str]: result txt files which contains corresponding
semantic segmentation images.
"""
mmcv.mkdir_or_exist(imgfile_prefix)
result_files = []
prog_bar = mmcv.ProgressBar(len(self))
for idx in range(len(self)):
result = results[idx]
filename = self.img_infos[idx]['filename']
basename = osp.splitext(osp.basename(filename))[0]
png_filename = osp.join(imgfile_prefix, f'{basename}.png')
# The index range of official requirement is from 0 to 150.
# But the index range of output is from 0 to 149.
# That is because we set reduce_zero_label=True.
result = result + 1
output = Image.fromarray(result.astype(np.uint8))
output.save(png_filename)
result_files.append(png_filename)
prog_bar.update()
return result_files
def format_results(self, results, imgfile_prefix=None, to_label_id=True):
"""Format the results into dir (standard format for ade20k evaluation).
Args:
results (list): Testing results of the dataset.
imgfile_prefix (str | None): The prefix of images files. It
includes the file path and the prefix of filename, e.g.,
"a/b/prefix". If not specified, a temp file will be created.
Default: None.
to_label_id (bool): whether convert output to label_id for
submission. Default: False
Returns:
tuple: (result_files, tmp_dir), result_files is a list containing
the image paths, tmp_dir is the temporal directory created
for saving json/png files when img_prefix is not specified.
"""
assert isinstance(results, list), 'results must be a list'
assert len(results) == len(self), (
'The length of results is not equal to the dataset len: '
f'{len(results)} != {len(self)}')
if imgfile_prefix is None:
tmp_dir = tempfile.TemporaryDirectory()
imgfile_prefix = tmp_dir.name
else:
tmp_dir = None
result_files = self.results2img(results, imgfile_prefix, to_label_id)
return result_files, tmp_dir