Datasets:
fix: script
Browse files
data/presentation-attack-detection-2d-dataset.csv
CHANGED
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@@ -1,15 +1,15 @@
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video,set_id,worker_id,age,gender,country
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-
000269e00f--64c8d84d089f4e44f6481bb0/3.mp4,000269e00f--64c8d84d089f4e44f6481bb0,87284a341d43afbbdab0e50ca251d0a4,29,MALE,TR
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-
000269e00f--64c8f4db4a10835184c95641/3.mp4,be29b530751176898fc789fd05a9c7f5,31,FEMALE,RU
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-
000269e00f--64c8f55c64b09d4014084391/3.mp4,44617ee2c5d73df66092a16d5f31cc01,31,MALE,RU
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-
000269e00f--64c9cbf134a9be2301431749/3.mp4,a584def9dac1981eab24fe5f49d14f41,20,FEMALE,RU
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-
000269e00f--64ca0aa684be481f7568360f/3.MOV,bd3d36b02696f6306ebbe24470e39360,33,NULL,KZ
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| 7 |
-
000269e00f--64ca72f2c38b125fffa93c6e/3.mp4,22b51caa31b5cbb85543724dd638161b,33,MALE,RU
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-
000269e00f--64caa8acb4858c670df55582/3.mp4,333563ad329ed488f987582afe1a08d8,23,FEMALE,RU
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| 9 |
-
000269e00f--64cb61c13dc862273921414f/3.mp4,2bc6b8bf0f8b96b5ca977264e23309c4,18,NULL,RU
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-
000269e00f--64cbccc402343312e74eccfb/3.mp4,666df1bb2ab0bbb8eadb2f56c139494a,44,FEMALE,RU
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-
000269e00f--64cce2f9747ca45dad369280/3.mp4,8a1401b507e0cd65b4d42d7dd71a64a2,38,FEMALE,RU
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-
000269e00f--64ce34be591a914f7a454dae/3.mp4,36277a2ea9a122d816b1b1b3e2eaa178,21,MALE,RU
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-
000269e00f--64cf6c2ca3e04150ef4c19c2/3.MOV,450ce6a2a97424d4ecae0e95df862ba5,23,FEMALE,RU
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-
000269e00f--64d1d284038f0820fecdab8b/3.mp4,81338ba7fc06c99471d04f99c4ee7740,38,MALE,RU
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-
000269e00f--64d25998571de06b0eecc774/3.mp4,08ac2144aacba85a377efedb9875b1c9,28,FEMALE,RU
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video,set_id,worker_id,age,gender,country
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+
000269e00f--64c8d84d089f4e44f6481bb0/3.mp4,000269e00f--64c8d84d089f4e44f6481bb0,000269e00f--64c8d84d089f4e44f6481bb0,87284a341d43afbbdab0e50ca251d0a4,29,MALE,TR
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| 3 |
+
000269e00f--64c8f4db4a10835184c95641/3.mp4,000269e00f--64c8f4db4a10835184c95641,be29b530751176898fc789fd05a9c7f5,31,FEMALE,RU
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| 4 |
+
000269e00f--64c8f55c64b09d4014084391/3.mp4,000269e00f--64c8f55c64b09d4014084391,44617ee2c5d73df66092a16d5f31cc01,31,MALE,RU
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+
000269e00f--64c9cbf134a9be2301431749/3.mp4,000269e00f--64c9cbf134a9be2301431749,a584def9dac1981eab24fe5f49d14f41,20,FEMALE,RU
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+
000269e00f--64ca0aa684be481f7568360f/3.MOV,000269e00f--64ca0aa684be481f7568360f,bd3d36b02696f6306ebbe24470e39360,33,NULL,KZ
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| 7 |
+
000269e00f--64ca72f2c38b125fffa93c6e/3.mp4,000269e00f--64ca72f2c38b125fffa93c6e,22b51caa31b5cbb85543724dd638161b,33,MALE,RU
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+
000269e00f--64caa8acb4858c670df55582/3.mp4,000269e00f--64caa8acb4858c670df55582,333563ad329ed488f987582afe1a08d8,23,FEMALE,RU
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| 9 |
+
000269e00f--64cb61c13dc862273921414f/3.mp4,000269e00f--64cb61c13dc862273921414f,2bc6b8bf0f8b96b5ca977264e23309c4,18,NULL,RU
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| 10 |
+
000269e00f--64cbccc402343312e74eccfb/3.mp4,000269e00f--64cbccc402343312e74eccfb,666df1bb2ab0bbb8eadb2f56c139494a,44,FEMALE,RU
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+
000269e00f--64cce2f9747ca45dad369280/3.mp4,000269e00f--64cce2f9747ca45dad369280,8a1401b507e0cd65b4d42d7dd71a64a2,38,FEMALE,RU
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+
000269e00f--64ce34be591a914f7a454dae/3.mp4,000269e00f--64ce34be591a914f7a454dae,36277a2ea9a122d816b1b1b3e2eaa178,21,MALE,RU
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+
000269e00f--64cf6c2ca3e04150ef4c19c2/3.MOV,000269e00f--64cf6c2ca3e04150ef4c19c2,450ce6a2a97424d4ecae0e95df862ba5,23,FEMALE,RU
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+
000269e00f--64d1d284038f0820fecdab8b/3.mp4,000269e00f--64d1d284038f0820fecdab8b,81338ba7fc06c99471d04f99c4ee7740,38,MALE,RU
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+
000269e00f--64d25998571de06b0eecc774/3.mp4,000269e00f--64d25998571de06b0eecc774,08ac2144aacba85a377efedb9875b1c9,28,FEMALE,RU
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presentation-attack-detection-2d-dataset.py
CHANGED
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@@ -60,25 +60,25 @@ class PresentationAttackDetection2dDataset(datasets.GeneratorBasedBuilder):
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def _generate_examples(self, attacks, annotations):
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annotations_df = pd.read_csv(annotations, sep=",")
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for idx, (image_path, image) in enumerate(attacks):
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-
if image_path.endswith(
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yield idx, {
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"photo": {"path": image_path, "bytes": image},
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"video": annotations_df.loc[
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-
annotations_df["set_id"].
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]["video"].values[0],
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"worker_id": annotations_df.loc[
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-
annotations_df["set_id"].
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]["worker_id"].values[0],
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"set_id": annotations_df.loc[
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-
annotations_df["set_id"].
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]["set_id"].values[0],
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"age": annotations_df.loc[
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-
annotations_df["set_id"].
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]["age"].values[0],
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"country": annotations_df.loc[
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-
annotations_df["set_id"].
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]["country"].values[0],
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"gender": annotations_df.loc[
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-
annotations_df["set_id"].
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]["gender"].values[0],
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}
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def _generate_examples(self, attacks, annotations):
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annotations_df = pd.read_csv(annotations, sep=",")
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for idx, (image_path, image) in enumerate(attacks):
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+
if image_path.endswith("jpg"):
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yield idx, {
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"photo": {"path": image_path, "bytes": image},
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"video": annotations_df.loc[
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+
annotations_df["set_id"].str.contains(image_path.split("/")[0])
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]["video"].values[0],
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"worker_id": annotations_df.loc[
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+
annotations_df["set_id"].str.contains(image_path.split("/")[0])
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]["worker_id"].values[0],
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"set_id": annotations_df.loc[
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+
annotations_df["set_id"].str.contains(image_path.split("/")[0])
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]["set_id"].values[0],
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"age": annotations_df.loc[
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+
annotations_df["set_id"].str.contains(image_path.split("/")[0])
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]["age"].values[0],
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"country": annotations_df.loc[
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+
annotations_df["set_id"].str.contains(image_path.split("/")[0])
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]["country"].values[0],
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"gender": annotations_df.loc[
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+
annotations_df["set_id"].str.contains(image_path.split("/")[0])
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]["gender"].values[0],
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}
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