refactor: script

selfie_and_video.py

@@ -1,22 +1,22 @@
-import io
-
 import datasets
 import pandas as pd
 
 _CITATION = """\
 @InProceedings{huggingface:dataset,
-title = {portrait_and_26_photos},
+title = {selfie_and_video},
 author = {TrainingDataPro},
 year = {2023}
 }
 """
 
 _DESCRIPTION = """\
-Each set includes 27 photos of people. Each person provided
-two types of photos: one photo in profile (portrait_1),
-and 26 photos from their life (photo_1, photo_2, …, photo_26).
+4000 people in this dataset. Each person took a selfie on a webcam,
+took a selfie on a mobile phone. In addition, people recorded video from
+the phone and from the webcam, on which they pronounced a given set of numbers.
+Includes folders corresponding to people in the dataset. Each folder includes
+8 files (4 images and 4 videos).
 """
-_NAME = 'portrait_and_26_photos'
+_NAME = 'selfie_and_video'
 
 _HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}"
 
@@ -25,40 +25,22 @@ _LICENSE = ""
 _DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/"
 
 
-class PortraitAnd26Photos(datasets.GeneratorBasedBuilder):
+class SelfieAndVideo(datasets.GeneratorBasedBuilder):
     """Small sample of image-text pairs"""
 
     def _info(self):
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=datasets.Features({
-                'portrait_1': datasets.Image(),
                 'photo_1': datasets.Image(),
                 'photo_2': datasets.Image(),
-                'photo_3': datasets.Image(),
-                'photo_4': datasets.Image(),
+                'video_3': datasets.Value('string'),
+                'video_4': datasets.Value('string'),
                 'photo_5': datasets.Image(),
                 'photo_6': datasets.Image(),
-                'photo_7': datasets.Image(),
-                'photo_8': datasets.Image(),
-                'photo_9': datasets.Image(),
-                'photo_10': datasets.Image(),
-                'photo_11': datasets.Image(),
-                'photo_12': datasets.Image(),
-                'photo_13': datasets.Image(),
-                'photo_14': datasets.Image(),
-                'photo_15': datasets.Image(),
-                'photo_16': datasets.Image(),
-                'photo_17': datasets.Image(),
-                'photo_18': datasets.Image(),
-                'photo_19': datasets.Image(),
-                'photo_20': datasets.Image(),
-                'photo_21': datasets.Image(),
-                'photo_22': datasets.Image(),
-                'photo_23': datasets.Image(),
-                'photo_24': datasets.Image(),
-                'photo_25': datasets.Image(),
-                'photo_26': datasets.Image(),
+                'video_7': datasets.Value('string'),
+                'video_8': datasets.Value('string'),
+                'set_id': datasets.Value('string'),
                 'worker_id': datasets.Value('string'),
                 'age': datasets.Value('int8'),
                 'country': datasets.Value('string'),
@@ -85,30 +67,39 @@ class PortraitAnd26Photos(datasets.GeneratorBasedBuilder):
         annotations_df = pd.read_csv(annotations, sep=',')
         images_data = pd.DataFrame(columns=['Link', 'Bytes'])
         for idx, (image_path, image) in enumerate(images):
-            images_data.loc[idx] = {'Link': image_path, 'Bytes': image.read()}
+            if image_path.lower().endswith('.jpg'):
+                images_data.loc[idx] = {
+                    'Link': image_path,
+                    'Bytes': image.read()
+                }
 
         annotations_df = pd.merge(annotations_df, images_data)
         for idx, worker_id in enumerate(pd.unique(annotations_df['WorkerId'])):
             annotation = annotations_df.loc[annotations_df['WorkerId'] ==
                                             worker_id]
-            annotation = annotation.sort_values(['Type'])
+            annotation = annotation.sort_values(['Link'])
             data = {
-                row[5]: {
-                    'path': row[6],
-                    'bytes': row[7]
-                } for row in annotation.itertuples()
+                (f'photo_{row[6][37]}' if row[6].lower().endswith('.jpg') else f'video_{row[6][37]}'):
+                    ({
+                        'path': row[6],
+                        'bytes': row[7]
+                    } if row[6].lower().endswith('.jpg') else row[6])
+                for row in annotation.itertuples()
             }
 
-            age = annotation.loc[annotation['Type'] ==
-                                 'portrait_1']['Age'].values[0]
-            country = annotation.loc[annotation['Type'] ==
-                                     'portrait_1']['Country'].values[0]
-            gender = annotation.loc[annotation['Type'] ==
-                                    'portrait_1']['Gender'].values[0]
+            age = annotation.loc[annotation['Link'].endswith(
+                '1.jpg')]['Age'].values[0]
+            country = annotation.loc[annotation['Link'].endswith(
+                '1.jpg')]['Country'].values[0]
+            gender = annotation.loc[annotation['Link'].endswith(
+                '1.jpg')]['Gender'].values[0]
+            set_id = annotation.loc[annotation['Link'].endswith(
+                '1.jpg')]['SetId'].values[0]
 
             data['worker_id'] = worker_id
             data['age'] = age
             data['country'] = country
             data['gender'] = gender
+            data['set_id'] = set_id
 
             yield idx, data