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

* 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

README.md

@@ -6,7 +6,7 @@ language_creators:
 languages:
 - en
 licenses:
-- unknown
+- cc-by-nc-nd-4.0
 multilinguality:
 - monolingual
 size_categories:
@@ -191,7 +191,7 @@ Shuo Yang, Ping Luo, Chen Change Loy and Xiaoou Tang
 
 ### Licensing Information
 
-[More Information Needed]
+[Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)](https://creativecommons.org/licenses/by-nc-nd/4.0/).
 
 ### Citation Information
 

dataset_infos.json

@@ -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}}
+{"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

@@ -21,7 +21,7 @@ import datasets
 
 _HOMEPAGE = "http://shuoyang1213.me/WIDERFACE/"
 
-_LICENSE = "Unknown"
+_LICENSE = "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"
 
 _CITATION = """\
 @inproceedings{yang2016wider,
@@ -43,10 +43,14 @@ we do not release bounding box ground truth for the test images. Users are
 required to submit final prediction files, which we shall proceed to evaluate.
 """
 
-_TRAIN_DOWNLOAD_URL = "https://drive.google.com/u/0/uc?id=15hGDLhsx8bLgLcIRD5DhYt5iBxnjNF1M&export=download"
-_TEST_DOWNLOAD_URL = "https://drive.google.com/u/0/uc?id=1HIfDbVEWKmsYKJZm4lchTBDLW5N7dY5T&export=download"
-_VALIDATION_DOWNLOAD_URL = "https://drive.google.com/u/0/uc?id=1GUCogbp16PMGa39thoMMeWxp7Rp5oM8Q&export=download"
-_ANNOT_DOWNLOAD_URL = "http://shuoyang1213.me/WIDERFACE/support/bbx_annotation/wider_face_split.zip"
+
+_REPO = "https://huggingface.co/datasets/wider_face/resolve/main/data"
+_URLS = {
+    "train": f"{_REPO}/WIDER_train.zip",
+    "validation": f"{_REPO}/WIDER_val.zip",
+    "test": f"{_REPO}/WIDER_test.zip",
+    "annot": f"{_REPO}/wider_face_split.zip",
+}
 
 
 class WiderFace(datasets.GeneratorBasedBuilder):
@@ -80,32 +84,30 @@ class WiderFace(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        train_dir, test_dir, validation_dir, annot_dir = dl_manager.download_and_extract(
-            [_TRAIN_DOWNLOAD_URL, _TEST_DOWNLOAD_URL, _VALIDATION_DOWNLOAD_URL, _ANNOT_DOWNLOAD_URL]
-        )
+        data_dir = dl_manager.download_and_extract(_URLS)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
                     "split": "train",
-                    "data_dir": train_dir,
-                    "annot_dir": annot_dir,
+                    "data_dir": data_dir["train"],
+                    "annot_dir": data_dir["annot"],
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
                     "split": "test",
-                    "data_dir": test_dir,
-                    "annot_dir": annot_dir,
+                    "data_dir": data_dir["test"],
+                    "annot_dir": data_dir["annot"],
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
                     "split": "val",
-                    "data_dir": validation_dir,
-                    "annot_dir": annot_dir,
+                    "data_dir": data_dir["validation"],
+                    "annot_dir": data_dir["annot"],
                 },
             ),
         ]