Update

requirements.txt

@@ -1 +1,3 @@
+# Python 3.10.6
 datasets
+Pillow

test.py

@@ -18,6 +18,8 @@
 import csv
 import json
 import os
+from typing import Dict, List
+from PIL import Image
 
 import datasets
 from datasets import DownloadManager
@@ -56,6 +58,19 @@ _URLS = {
 _BASE_URL = ""
 
 
+def get_download_url(config_name: str, partition: str) -> str:
+    """Get download URL based on config name and parition (train/dev/test)
+
+    Args:
+        config_name (str): can be "v1", "v2",...
+        partition (str): can be "train", "dev" or "test"
+
+    Returns:
+        str: URL to download file
+    """
+    return f"https://huggingface.co/datasets/RGBD-SOD/test/tree/main/data{config_name}/{partition}.zip"
+
+
 # TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
 class Test(datasets.GeneratorBasedBuilder):
     """TODO: Short description of my dataset."""
@@ -98,6 +113,7 @@ class Test(datasets.GeneratorBasedBuilder):
                     "depth": datasets.Image(),
                     "rgb": datasets.Image(),
                     "gt": datasets.Image(),
+                    "name": datasets.Value("string"),
                     # These are the features of your dataset like images, labels ...
                 }
             ),  # Here we define them above because they are different between the two configurations
@@ -121,52 +137,48 @@ class Test(datasets.GeneratorBasedBuilder):
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         urls = _URLS[self.config.name]
         data_dir = dl_manager.download_and_extract(urls)
+        train_dir = dl_manager.download_and_extract(
+            get_download_url(self.config.name, "train")
+        )
+        dev_dir = dl_manager.download_and_extract(
+            get_download_url(self.config.name, "dev")
+        )
+        # test_dir = dl_manager.download_and_extract(
+        #     get_download_url(self.config.name, "test")
+        # )
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "train.jsonl"),
-                    "split": "train",
-                },
+                gen_kwargs={"dir_path": train_dir},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "dev.jsonl"),
-                    "split": "dev",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "test.jsonl"),
-                    "split": "test",
-                },
+                gen_kwargs={"dir_path": dev_dir},
             ),
+            # datasets.SplitGenerator(
+            #     name=datasets.Split.TEST,
+            #     # These kwargs will be passed to _generate_examples
+            #     gen_kwargs={"dir_path": test_dir},
+            # ),
         ]
 
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filepath: str, split: str):
+    def _generate_examples(self, dir_path: str):
         # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
         # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        with open(filepath, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                data = json.loads(row)
-                if self.config.name == "first_domain":
-                    # Yields examples as (key, example) tuples
-                    yield key, {
-                        "sentence": data["sentence"],
-                        "option1": data["option1"],
-                        "answer": "" if split == "test" else data["answer"],
-                    }
-                else:
-                    yield key, {
-                        "sentence": data["sentence"],
-                        "option2": data["option2"],
-                        "second_domain_answer": ""
-                        if split == "test"
-                        else data["second_domain_answer"],
-                    }
+        with open(os.path.join(dir_path, "metadata.json"), "r") as f:
+            json_object = json.load(f)
+
+        metadata: List[Dict[str, str]] = json_object["metadata"]
+
+        for key, row in enumerate(metadata):
+            yield key, {
+                "name": row["name"],
+                "rgb": Image.open(os.path.join(dir_path, metadata["rgb"]), mode="RGB"),
+                "gt": Image.open(os.path.join(dir_path, metadata["gt"]), mode="L"),
+                "depth": Image.open(
+                    os.path.join(dir_path, metadata["depth"]), mode="L"
+                ),
+            }