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albertvillanova HF staff commited on
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1 Parent(s): ba0019b

Replace data URLs in wider_face dataset once hosted on the Hub (#4469)

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* Replace data URL once hosted on the Hub

* Update metadata JSON

* Add license

* Update metadata JSON

Commit from https://github.com/huggingface/datasets/commit/eae58c0361d0a8dd4219126492ba9526067d8b8e

Files changed (3) hide show
  1. README.md +2 -2
  2. dataset_infos.json +1 -1
  3. wider_face.py +16 -14
README.md CHANGED
@@ -6,7 +6,7 @@ language_creators:
6
  languages:
7
  - en
8
  licenses:
9
- - unknown
10
  multilinguality:
11
  - monolingual
12
  size_categories:
@@ -191,7 +191,7 @@ Shuo Yang, Ping Luo, Chen Change Loy and Xiaoou Tang
191
 
192
  ### Licensing Information
193
 
194
- [More Information Needed]
195
 
196
  ### Citation Information
197
 
 
6
  languages:
7
  - en
8
  licenses:
9
+ - cc-by-nc-nd-4.0
10
  multilinguality:
11
  - monolingual
12
  size_categories:
 
191
 
192
  ### Licensing Information
193
 
194
+ [Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)](https://creativecommons.org/licenses/by-nc-nd/4.0/).
195
 
196
  ### Citation Information
197
 
dataset_infos.json CHANGED
@@ -1 +1 @@
1
- {"default": {"description": "WIDER FACE dataset is a face detection benchmark dataset, of which images are\nselected from the publicly available WIDER dataset. We choose 32,203 images and\nlabel 393,703 faces with a high degree of variability in scale, pose and\nocclusion as depicted in the sample images. WIDER FACE dataset is organized\nbased on 61 event classes. For each event class, we randomly select 40%/10%/50%\ndata as training, validation and testing sets. We adopt the same evaluation\nmetric employed in the PASCAL VOC dataset. Similar to MALF and Caltech datasets,\nwe do not release bounding box ground truth for the test images. Users are\nrequired to submit final prediction files, which we shall proceed to evaluate.\n", "citation": "@inproceedings{yang2016wider,\n Author = {Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou},\n Booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},\n Title = {WIDER FACE: A Face Detection Benchmark},\n Year = {2016}}\n", "homepage": "http://shuoyang1213.me/WIDERFACE/", "license": "Unknown", "features": {"image": {"id": null, "_type": "Image"}, "faces": {"feature": {"bbox": {"feature": {"dtype": "float32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}, "blur": {"num_classes": 3, "names": ["clear", "normal", "heavy"], "names_file": null, "id": null, "_type": "ClassLabel"}, "expression": {"num_classes": 2, "names": ["typical", "exaggerate"], "names_file": null, "id": null, "_type": "ClassLabel"}, "illumination": {"num_classes": 2, "names": ["normal", "exaggerate "], "names_file": null, "id": null, "_type": "ClassLabel"}, "occlusion": {"num_classes": 3, "names": ["no", "partial", "heavy"], "names_file": null, "id": null, "_type": "ClassLabel"}, "pose": {"num_classes": 2, "names": ["typical", "atypical"], "names_file": null, "id": null, "_type": "ClassLabel"}, "invalid": {"dtype": "bool", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wider_face", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 11996002, "num_examples": 12880, "dataset_name": "wider_face"}, "test": {"name": "test", "num_bytes": 3796193, "num_examples": 16097, "dataset_name": "wider_face"}, "validation": {"name": "validation", "num_bytes": 2985369, "num_examples": 3226, "dataset_name": "wider_face"}}, "download_checksums": {"https://drive.google.com/u/0/uc?id=15hGDLhsx8bLgLcIRD5DhYt5iBxnjNF1M&export=download": {"num_bytes": 1465602149, "checksum": "e23b76129c825cafae8be944f65310b2e1ba1c76885afe732f179c41e5ed6d59"}, "https://drive.google.com/u/0/uc?id=1HIfDbVEWKmsYKJZm4lchTBDLW5N7dY5T&export=download": {"num_bytes": 1844140520, "checksum": "3b0313e11ea292ec58894b47ac4c0503b230e12540330845d70a7798241f88d3"}, "https://drive.google.com/u/0/uc?id=1GUCogbp16PMGa39thoMMeWxp7Rp5oM8Q&export=download": {"num_bytes": 362752168, "checksum": "f9efbd09f28c5d2d884be8c0eaef3967158c866a593fc36ab0413e4b2a58a17a"}, "http://shuoyang1213.me/WIDERFACE/support/bbx_annotation/wider_face_split.zip": {"num_bytes": 3591642, "checksum": "c7561e4f5e7a118c249e0a5c5c902b0de90bbf120d7da9fa28d99041f68a8a5c"}}, "download_size": 3676086479, "post_processing_size": null, "dataset_size": 18777564, "size_in_bytes": 3694864043}}
 
1
+ {"default": {"description": "WIDER FACE dataset is a face detection benchmark dataset, of which images are\nselected from the publicly available WIDER dataset. We choose 32,203 images and\nlabel 393,703 faces with a high degree of variability in scale, pose and\nocclusion as depicted in the sample images. WIDER FACE dataset is organized\nbased on 61 event classes. For each event class, we randomly select 40%/10%/50%\ndata as training, validation and testing sets. We adopt the same evaluation\nmetric employed in the PASCAL VOC dataset. Similar to MALF and Caltech datasets,\nwe do not release bounding box ground truth for the test images. Users are\nrequired to submit final prediction files, which we shall proceed to evaluate.\n", "citation": "@inproceedings{yang2016wider,\n Author = {Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou},\n Booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},\n Title = {WIDER FACE: A Face Detection Benchmark},\n Year = {2016}}\n", "homepage": "http://shuoyang1213.me/WIDERFACE/", "license": "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "faces": {"feature": {"bbox": {"feature": {"dtype": "float32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}, "blur": {"num_classes": 3, "names": ["clear", "normal", "heavy"], "id": null, "_type": "ClassLabel"}, "expression": {"num_classes": 2, "names": ["typical", "exaggerate"], "id": null, "_type": "ClassLabel"}, "illumination": {"num_classes": 2, "names": ["normal", "exaggerate "], "id": null, "_type": "ClassLabel"}, "occlusion": {"num_classes": 3, "names": ["no", "partial", "heavy"], "id": null, "_type": "ClassLabel"}, "pose": {"num_classes": 2, "names": ["typical", "atypical"], "id": null, "_type": "ClassLabel"}, "invalid": {"dtype": "bool", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wider_face", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 12049881, "num_examples": 12880, "dataset_name": "wider_face"}, "test": {"name": "test", "num_bytes": 3761103, "num_examples": 16097, "dataset_name": "wider_face"}, "validation": {"name": "validation", "num_bytes": 2998735, "num_examples": 3226, "dataset_name": "wider_face"}}, "download_checksums": {"https://huggingface.co/datasets/wider_face/resolve/main/data/WIDER_train.zip": {"num_bytes": 1465602149, "checksum": "e23b76129c825cafae8be944f65310b2e1ba1c76885afe732f179c41e5ed6d59"}, "https://huggingface.co/datasets/wider_face/resolve/main/data/WIDER_val.zip": {"num_bytes": 362752168, "checksum": "f9efbd09f28c5d2d884be8c0eaef3967158c866a593fc36ab0413e4b2a58a17a"}, "https://huggingface.co/datasets/wider_face/resolve/main/data/WIDER_test.zip": {"num_bytes": 1844140520, "checksum": "3b0313e11ea292ec58894b47ac4c0503b230e12540330845d70a7798241f88d3"}, "https://huggingface.co/datasets/wider_face/resolve/main/data/wider_face_split.zip": {"num_bytes": 3591642, "checksum": "c7561e4f5e7a118c249e0a5c5c902b0de90bbf120d7da9fa28d99041f68a8a5c"}}, "download_size": 3676086479, "post_processing_size": null, "dataset_size": 18809719, "size_in_bytes": 3694896198}}
wider_face.py CHANGED
@@ -21,7 +21,7 @@ import datasets
21
 
22
  _HOMEPAGE = "http://shuoyang1213.me/WIDERFACE/"
23
 
24
- _LICENSE = "Unknown"
25
 
26
  _CITATION = """\
27
  @inproceedings{yang2016wider,
@@ -43,10 +43,14 @@ we do not release bounding box ground truth for the test images. Users are
43
  required to submit final prediction files, which we shall proceed to evaluate.
44
  """
45
 
46
- _TRAIN_DOWNLOAD_URL = "https://drive.google.com/u/0/uc?id=15hGDLhsx8bLgLcIRD5DhYt5iBxnjNF1M&export=download"
47
- _TEST_DOWNLOAD_URL = "https://drive.google.com/u/0/uc?id=1HIfDbVEWKmsYKJZm4lchTBDLW5N7dY5T&export=download"
48
- _VALIDATION_DOWNLOAD_URL = "https://drive.google.com/u/0/uc?id=1GUCogbp16PMGa39thoMMeWxp7Rp5oM8Q&export=download"
49
- _ANNOT_DOWNLOAD_URL = "http://shuoyang1213.me/WIDERFACE/support/bbx_annotation/wider_face_split.zip"
 
 
 
 
50
 
51
 
52
  class WiderFace(datasets.GeneratorBasedBuilder):
@@ -80,32 +84,30 @@ class WiderFace(datasets.GeneratorBasedBuilder):
80
  )
81
 
82
  def _split_generators(self, dl_manager):
83
- train_dir, test_dir, validation_dir, annot_dir = dl_manager.download_and_extract(
84
- [_TRAIN_DOWNLOAD_URL, _TEST_DOWNLOAD_URL, _VALIDATION_DOWNLOAD_URL, _ANNOT_DOWNLOAD_URL]
85
- )
86
  return [
87
  datasets.SplitGenerator(
88
  name=datasets.Split.TRAIN,
89
  gen_kwargs={
90
  "split": "train",
91
- "data_dir": train_dir,
92
- "annot_dir": annot_dir,
93
  },
94
  ),
95
  datasets.SplitGenerator(
96
  name=datasets.Split.TEST,
97
  gen_kwargs={
98
  "split": "test",
99
- "data_dir": test_dir,
100
- "annot_dir": annot_dir,
101
  },
102
  ),
103
  datasets.SplitGenerator(
104
  name=datasets.Split.VALIDATION,
105
  gen_kwargs={
106
  "split": "val",
107
- "data_dir": validation_dir,
108
- "annot_dir": annot_dir,
109
  },
110
  ),
111
  ]
 
21
 
22
  _HOMEPAGE = "http://shuoyang1213.me/WIDERFACE/"
23
 
24
+ _LICENSE = "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"
25
 
26
  _CITATION = """\
27
  @inproceedings{yang2016wider,
 
43
  required to submit final prediction files, which we shall proceed to evaluate.
44
  """
45
 
46
+
47
+ _REPO = "https://huggingface.co/datasets/wider_face/resolve/main/data"
48
+ _URLS = {
49
+ "train": f"{_REPO}/WIDER_train.zip",
50
+ "validation": f"{_REPO}/WIDER_val.zip",
51
+ "test": f"{_REPO}/WIDER_test.zip",
52
+ "annot": f"{_REPO}/wider_face_split.zip",
53
+ }
54
 
55
 
56
  class WiderFace(datasets.GeneratorBasedBuilder):
 
84
  )
85
 
86
  def _split_generators(self, dl_manager):
87
+ data_dir = dl_manager.download_and_extract(_URLS)
 
 
88
  return [
89
  datasets.SplitGenerator(
90
  name=datasets.Split.TRAIN,
91
  gen_kwargs={
92
  "split": "train",
93
+ "data_dir": data_dir["train"],
94
+ "annot_dir": data_dir["annot"],
95
  },
96
  ),
97
  datasets.SplitGenerator(
98
  name=datasets.Split.TEST,
99
  gen_kwargs={
100
  "split": "test",
101
+ "data_dir": data_dir["test"],
102
+ "annot_dir": data_dir["annot"],
103
  },
104
  ),
105
  datasets.SplitGenerator(
106
  name=datasets.Split.VALIDATION,
107
  gen_kwargs={
108
  "split": "val",
109
+ "data_dir": data_dir["validation"],
110
+ "annot_dir": data_dir["annot"],
111
  },
112
  ),
113
  ]