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DefTruth / torchlm

💎A high level pipeline for face landmarks detection, it supports training, evaluating, exporting, inference(Python/C++) and 100+ data augmentations, can easily install via pip.
https://github.com/DefTruth/torchlm
MIT License
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Error on Converting 300W dataset in class Landmarks300WConverter with message UFuncTypeError: Cannot cast ufunc 'subtract' output... #60

Open nunenuh opened 2 years ago

nunenuh commented 2 years ago

Example code

from torchlm.data import LandmarksWFLWConverter, Landmarks300WConverter
# setup your path to the original downloaded dataset from official 
converter = Landmarks300WConverter(
    data_dir="/data/extended/landmark/ibug_300W_dlib/", save_dir="/data/extended/landmark/ibug_300W_dlib/converted",
    extend=0.2, rebuild=True, target_size=256, keep_aspect=False,
    force_normalize=True, force_absolute_path=True
)
converter.convert()
converter.show(count=30)  # show you some converted images with landmarks for debugging

Error Message

Converting 300W Train Annotations:   0%|                                                                                                                                          | 0/3148 [00:00<?, ?it/s]
---------------------------------------------------------------------------
UFuncTypeError                            Traceback (most recent call last)
Input In [1], in <cell line: 8>()
      2 # setup your path to the original downloaded dataset from official 
      3 converter = Landmarks300WConverter(
      4     data_dir="/data/extended/landmark/ibug_300W_dlib//", save_dir="/data/extended/landmark/ibug_300W_dlib/converted",
      5     extend=0.2, rebuild=True, target_size=256, keep_aspect=False,
      6     force_normalize=True, force_absolute_path=True
      7 )
----> 8 converter.convert()
      9 converter.show(count=30)

File /opt/anaconda/envs/facial/lib/python3.9/site-packages/torchlm/data/_converters.py:329, in Landmarks300WConverter.convert(self)
    322 test_anno_file = open(self.save_test_annotation_path, "w")
    324 for annotation in tqdm.tqdm(
    325         self.train_annotations,
    326         colour="GREEN",
    327         desc="Converting 300W Train Annotations"
    328 ):
--> 329     crop, landmarks, new_img_name = self._process_annotation(annotation=annotation)
    330     if crop is None or landmarks is None:
    331         continue

File /opt/anaconda/envs/facial/lib/python3.9/site-packages/torchlm/data/_converters.py:493, in Landmarks300WConverter._process_annotation(self, annotation)
    491 crop = image[int(ymin):int(ymax), int(xmin):int(xmax), :]
    492 # adjust according to left-top corner
--> 493 landmarks[:, 0] -= float(xmin)
    494 landmarks[:, 1] -= float(ymin)
    496 if self.target_size is not None and self.resize_op is not None:

UFuncTypeError: Cannot cast ufunc 'subtract' output from dtype('float64') to dtype('int64') with casting rule 'same_kind'

Solution

Change this line

# adjust according to left-top corner
landmarks[:, 0] -= float(xmin)
landmarks[:, 1] -= float(ymin)

Use this line instead

# adjust according to left-top corner
landmarks[:, 0] = landmarks[:, 0] - float(xmin)
landmarks[:, 1] = landmarks[:, 1] - float(ymin)

Environment