refactor: data and script

FaceSegmentation.py

@@ -0,0 +1,76 @@
+import datasets
+import pandas as pd
+
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {FaceSegmentation},
+author = {TrainingDataPro},
+year = {2023}
+}
+"""
+
+_DESCRIPTION = """\
+An example of a dataset that we've collected for a photo edit App.
+The dataset includes 20 selfies of people (man and women)
+in segmentation masks and their visualisations.
+"""
+_NAME = 'FaceSegmentation'
+
+_HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}"
+
+_LICENSE = ""
+
+_DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/"
+
+
+class FaceSegmentation(datasets.GeneratorBasedBuilder):
+    """Small sample of image-text pairs"""
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({
+                'image': datasets.Image(),
+                'mask': datasets.Image(),
+                'id': datasets.Value('string'),
+                'gender': datasets.Value('string'),
+                'age': datasets.Value('int8')
+            }),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        images = dl_manager.download(f"{_DATA}images.tar.gz")
+        masks = dl_manager.download(f"{_DATA}masks.tar.gz")
+        annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
+        images = dl_manager.iter_archive(images)
+        masks = dl_manager.iter_archive(masks)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN,
+                                    gen_kwargs={
+                                        "images": images,
+                                        'masks': masks,
+                                        'annotations': annotations
+                                    }),
+        ]
+
+    def _generate_examples(self, images, masks, annotations):
+        annotations_df = pd.read_csv(annotations, sep=';')
+
+        for idx, ((image_path, image),
+                  (mask_path, mask)) in enumerate(zip(images, masks)):
+            yield idx, {
+                "image": {
+                    "path": image_path,
+                    "bytes": image.read()
+                },
+                "mask": {
+                    "path": mask_path,
+                    "bytes": mask.read()
+                },
+                'id': annotations_df['id'].iloc[idx],
+                'gender': annotations_df['gender'].iloc[idx],
+                'age': annotations_df['age'].iloc[idx]
+            }

Face_Segmentation_20.csv

@@ -1,21 +0,0 @@
-img_name,masks_name
-img/0.jpg,masks/0.jpg
-img/1.jpg,masks/1.jpg
-img/2.jpg,masks/2.jpg
-img/3.jpg,masks/3.jpg
-img/4.jpg,masks/4.jpg
-img/5.jpg,masks/5.jpg
-img/6.jpg,masks/6.jpg
-img/7.jpg,masks/7.jpg
-img/8.jpg,masks/8.jpg
-img/9.jpg,masks/9.jpg
-img/10.jpg,masks/10.jpg
-img/11.jpg,masks/11.jpg
-img/12.jpg,masks/12.jpg
-img/13.jpg,masks/13.jpg
-img/14.jpg,masks/14.jpg
-img/15.jpg,masks/15.jpg
-img/16.jpg,masks/16.jpg
-img/17.jpg,masks/17.jpg
-img/18.jpg,masks/18.jpg
-img/19.jpg,masks/19.jpg

data/FaceSegmentation.csv

@@ -0,0 +1,21 @@
+id;gender;age;images;masks
+060002_4_028450;FEMALE;30;0.jpg;0.jpg
+060003_4_028451;FEMALE;65;1.jpg;1.jpg
+060004_4_028452;MALE;31;2.jpg;2.jpg
+060005_4_023834;FEMALE;33;3.jpg;3.jpg
+060006_4_015021;FEMALE;39;4.jpg;4.jpg
+060009_4_019350;FEMALE;21;5.jpg;5.jpg
+060012_4_020004;MALE;27;6.jpg;6.jpg
+060013_4_014380;MALE;34;7.jpg;7.jpg
+060014_4_016695;MALE;43;8.jpg;8.jpg
+060019_4_028457;MALE;33;9.jpg;9.jpg
+060020_3_024801;NONE;28;10.jpg;10.jpg
+060027_4_025986;FEMALE;36;11.jpg;11.jpg
+060028_4_022580;NONE;25;12.jpg;12.jpg
+060032_4_027166;MALE;28;13.jpg;13.jpg
+060033_4_028462;MALE;19;14.jpg;14.jpg
+060037_4_028465;FEMALE;23;15.jpg;15.jpg
+060038_4_028466;MALE;19;16.jpg;16.jpg
+060040_4_015000;FEMALE;39;17.jpg;17.jpg
+060043_4_028470;FEMALE;19;18.jpg;18.jpg
+060047_4_027403;MALE;25;19.jpg;19.jpg

img/0.jpg → data/images.tar.gz

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bf01e24cebf11b94205d74f91f9576a88a7192c37274757212debc1fb99855d8
-size 1860303
+oid sha256:459515c556e6d0ab1f1cf0f3f03d593e5c61905877abd9997076e51e44b05152
+size 43055161

img/11.jpg → data/masks.tar.gz

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:735e3067a810a67aec0441f49051b6874b25ff1b06dbf37709fc0aa95ae91c31
-size 237737
+oid sha256:f355f1f7e3ac9807c6adc99b2eddde8e76bf06b2f0f4e851c4f494986cd9ffd9
+size 1038283