refactor: script and readme

README.md

@@ -1,5 +1,39 @@
 ---
 license: cc-by-nc-nd-4.0
+dataset_info:
+  features:
+  - name: photo_1
+    dtype: image
+  - name: photo_2
+    dtype: image
+  - name: video_3
+    dtype: string
+  - name: video_4
+    dtype: string
+  - name: photo_5
+    dtype: image
+  - name: photo_6
+    dtype: image
+  - name: video_7
+    dtype: string
+  - name: video_8
+    dtype: string
+  - name: set_id
+    dtype: string
+  - name: worker_id
+    dtype: string
+  - name: age
+    dtype: int8
+  - name: country
+    dtype: string
+  - name: gender
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 49771508
+    num_examples: 10
+  download_size: 829589647
+  dataset_size: 49771508
 ---
 # Selfies and video dataset
 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.

selfie_and_video.py

@@ -52,7 +52,7 @@ class SelfieAndVideo(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        images = dl_manager.download(f"{_DATA}images.tar.gz")
+        images = dl_manager.download(f"{_DATA}data.tar.gz")
         annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
         images = dl_manager.iter_archive(images)
         return [
@@ -64,7 +64,7 @@ class SelfieAndVideo(datasets.GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, images, annotations):
-        annotations_df = pd.read_csv(annotations, sep=',')
+        annotations_df = pd.read_csv(annotations, sep=';')
         images_data = pd.DataFrame(columns=['Link', 'Bytes'])
         for idx, (image_path, image) in enumerate(images):
             if image_path.lower().endswith('.jpg'):
@@ -73,28 +73,32 @@ class SelfieAndVideo(datasets.GeneratorBasedBuilder):
                     'Bytes': image.read()
                 }
 
-        annotations_df = pd.merge(annotations_df, images_data)
+        annotations_df = pd.merge(annotations_df,
+                                  images_data,
+                                  on=['Link'],
+                                  how='left')
         for idx, worker_id in enumerate(pd.unique(annotations_df['WorkerId'])):
             annotation = annotations_df.loc[annotations_df['WorkerId'] ==
                                             worker_id]
             annotation = annotation.sort_values(['Link'])
             data = {
-                (f'photo_{row[6][37]}' if row[6].lower().endswith('.jpg') else f'video_{row[6][37]}'):
+                (f'photo_{row[7][37]}' if row[7].lower().endswith('.jpg') else f'video_{row[7][37]}'):
                     ({
-                        'path': row[6],
-                        'bytes': row[7]
-                    } if row[6].lower().endswith('.jpg') else row[6])
+                        'path': row[7],
+                        'bytes': row[8]
+                    } if row[7].lower().endswith('.jpg') else row[7])
                 for row in annotation.itertuples()
             }
+            print(annotation.head(8))
 
-            age = annotation.loc[annotation['Link'].endswith(
+            age = annotation.loc[annotation['Link'].str.lower().str.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]
+            country = annotation.loc[annotation['Link'].str.lower().str.
+                                     endswith('1.jpg')]['Country'].values[0]
+            gender = annotation.loc[annotation['Link'].str.lower().str.
+                                    endswith('1.jpg')]['Gender'].values[0]
+            set_id = annotation.loc[annotation['Link'].str.lower().str.
+                                    endswith('1.jpg')]['SetId'].values[0]
 
             data['worker_id'] = worker_id
             data['age'] = age