fix: update draft script

ui_refexp.py

@@ -12,7 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""TODO: Add a description here."""
+"""Dataset script for UI Referring Expressions based on the UIBert RefExp dataset."""
 
 
 import csv
@@ -47,17 +47,27 @@ _HOMEPAGE = "https://github.com/google-research-datasets/uibert"
 # TODO: Add the licence for the dataset here if you can find it
 _LICENSE = "CC BY 4.0"
 
-# TODO: Add link to the official dataset URLs here
+# Add link to the official dataset URLs here
 # The HuggingFace dataset library don't host the datasets but only point to the original files
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _DATA_URLs = {
-    "ui_refexp": "https://huggingface.co/datasets/ncoop57/rico_captions/resolve/main/captions_hierarchies_images.zip",
+    "ui_refexp": {
+        "images": "https://huggingface.co/datasets/ncoop57/rico_captions/resolve/main/captions_hierarchies_images.zip",
+    }
+}
+
+_METADATA_URLS = {
+    "ui_refexp": {
+        "train": "https://github.com/google-research-datasets/uibert/raw/main/ref_exp/train.tfrecord",
+        "validation": "https://github.com/google-research-datasets/uibert/raw/main/ref_exp/dev.tfrecord",
+        "test": "https://github.com/google-research-datasets/uibert/raw/main/ref_exp/test.tfrecord"
+    }
 }
 
 
 # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
 class UIRefExp(datasets.GeneratorBasedBuilder):
-    """TODO: Short description of my dataset."""
+    """Dataset with (image, question, answer) fields derive from UIBert RefExp."""
 
     VERSION = datasets.Version("1.1.0")
 
@@ -72,12 +82,13 @@ class UIRefExp(datasets.GeneratorBasedBuilder):
     # You will be able to load one or the other configurations in the following list with
     # data = datasets.load_dataset('my_dataset', 'first_domain')
     # data = datasets.load_dataset('my_dataset', 'second_domain')
-    # BUILDER_CONFIGS = [
-    #     datasets.BuilderConfig(
-    #         name="ui_refexp",
-    #         version=VERSION,
-    #         description="Contains 66k+ unique UI screens. For each UI, we present a screenshot (JPG file) and the text shown on the screen that was extracted using an OCR model.",
-    #     ),
+    BUILDER_CONFIGS = [
+         datasets.BuilderConfig(
+             name="ui_refexp",
+             version=VERSION,
+             description="Contains 66k+ unique UI screens. For each UI, we present a screenshot (JPG file) and the text shown on the screen that was extracted using an OCR model.",
+         )
+    #    ,
     #     # datasets.BuilderConfig(
     #     #     name="screenshots_captions_filtered",
     #     #     version=VERSION,
@@ -85,22 +96,21 @@ class UIRefExp(datasets.GeneratorBasedBuilder):
     #     # ),
     # ]
 
-    # DEFAULT_CONFIG_NAME = "screenshots_captions_filtered"
+    DEFAULT_CONFIG_NAME = "screenshots_captions_filtered"
 
     def _info(self):
         features = datasets.Features(
             {
-                "screenshot_path": datasets.Value("string"),
-                "caption": datasets.Value("string"),
-                # This is a JSON obj, but will be coded as a string
-                "hierarchy": datasets.Value("string"),
+                "screenshot": datasets.Image(),
+                "prompt": datasets.Value("string"), # click the search button next to menu drawer at the top of the screen
+                "target_bounding_box": dict, # [xmin, ymin, xmax, ymax], normalized screen reference values between 0 and 1
             }
         )
 
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=features,
-            supervised_keys=None,
+            supervised_keys=("screenshot","prompt", "target_bounding_box"),
             homepage=_HOMEPAGE,
             license=_LICENSE,
             citation=_CITATION,
@@ -108,22 +118,43 @@ class UIRefExp(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
         # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
 
         # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         my_urls = _DATA_URLs[self.config.name]
-        data_dir = dl_manager.download_and_extract(my_urls)
+        image_archive = dl_manager.download(my_urls)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "root_dir": data_dir,
+                    "tfrecords_file": , 
+                    "images": dl_manager.iter_archive(archive_path),
                     "split": "train",
+                    
                 },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "root_dir": data_dir,
+                    "images": dl_manager.iter_archive(archive_path),
+                    "split": "validation",
+                },                
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "root_dir": data_dir,
+                    "images": dl_manager.iter_archive(archive_path),
+                    "split": "test",
+                },                
             )
         ]