Update beyond_web_scraping.py

beyond_web_scraping.py

@@ -19,9 +19,9 @@ import datasets
 import json
 from huggingface_hub import hf_hub_url
 
-_INPUT_CSV = "fairface_labeled_val.csv"
-_INPUT_IMAGES_125 = 'fairface_val_images_125'
-_REPO_ID = "nlphuji/fairface_val_padding_125"
+_INPUT_CSV = "test_set.csv"
+_INPUT_IMAGES = 'geode_test_images'
+_REPO_ID = "nlphuji/beyond_web_scraping"
 
 class Dataset(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.1.0")
@@ -34,12 +34,21 @@ class Dataset(datasets.GeneratorBasedBuilder):
             features=datasets.Features(
                  {
                  "image": datasets.Image(),
-                "file": datasets.Value('string'),
-                "age": datasets.Value('string'),
-                "gender": datasets.Value('string'),
-                "race": datasets.Value('string'),
-                "service_test": datasets.Value('string'),
-                "image_name": datasets.Value('string'),
+                "file_path": datasets.Value('string'),
+                "object": datasets.Value('string'),
+                "region": datasets.Value('string'),
+                "ip_country": datasets.Value('string'),
+                "date": datasets.Value('string'),
+                "make": datasets.Value('string'),
+                 "make": datasets.Value('string'),
+                 "model": datasets.Value('string'),
+                 "gps_position": datasets.Value('string'),
+                 "gps_altitude": datasets.Value('string'),
+                 "resolution": datasets.Value('string'),
+                 "licence_plate": datasets.Value('string'),
+                 "people_in_background": datasets.Value('string'),
+                 "tree_tag": datasets.Value('string'),
+                 "short_file_path": datasets.Value('string'),
                 }
             ),
             task_templates=[],
@@ -51,7 +60,7 @@ class Dataset(datasets.GeneratorBasedBuilder):
         repo_id = _REPO_ID
         data_dir_125 = dl_manager.download_and_extract({
             "examples_csv": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=_INPUT_CSV),
-            "images_dir": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=f"{_INPUT_IMAGES_125}.zip")
+            "images_dir": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=f"{_INPUT_IMAGES}.zip")
         })
 
         return [datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=data_dir_125)]
@@ -63,6 +72,6 @@ class Dataset(datasets.GeneratorBasedBuilder):
 
         for r_idx, r in df.iterrows():
             r_dict = r.to_dict()
-            image_path = os.path.join(images_dir, _INPUT_IMAGES_125, r_dict['image_name'])
+            image_path = os.path.join(images_dir, _INPUT_IMAGES, r_dict['file_path'])
             r_dict['image'] = image_path
             yield r_idx, r_dict