add object detection config

NIH-Chest-X-ray-dataset.py

@@ -51,10 +51,10 @@ _REPO = "https://huggingface.co/datasets/alkzar90/NIH-Chest-X-ray-dataset/resolv
 
 
 _IMAGE_URLS = [
-	f"{_REPO}/images/images_001.zip",
-	f"{_REPO}/images/images_003.zip",
-	f"{_REPO}/images/images_004.zip",
-	f"{_REPO}/images/images_005.zip"
+	f"{_REPO}/images/images_001.zip"
+#	f"{_REPO}/images/images_003.zip",
+#	f"{_REPO}/images/images_004.zip",
+#	f"{_REPO}/images/images_005.zip"
 	#'https://huggingface.co/datasets/alkzar90/NIH-Chest-X-ray-dataset/resolve/main/dummy/0.0.0/images_001.tar.gz',
 	#'https://huggingface.co/datasets/alkzar90/NIH-Chest-X-ray-dataset/resolve/main/dummy/0.0.0/images_002.tar.gz'
 ]
@@ -90,7 +90,7 @@ _NAMES = list(_LABEL2IDX.keys())
 
 
 class ChestXray14Config(datasets.BuilderConfig):
-	"""allala"""
+	"""NIH Image Chest X-ray14 configuration."""
 	
 	def __init__(self, name, **kwargs):
 	    super(ChestXray14Config, self).__init__(
@@ -103,7 +103,7 @@ class ChestXray14Config(datasets.BuilderConfig):
 
 
 class ChestXray14(datasets.GeneratorBasedBuilder):
-	"""NIH Image Chest X-ray dataset."""
+	"""NIH Image Chest X-ray14 dataset."""
 
 
 	BUILDER_CONFIGS = [
@@ -121,11 +121,28 @@ class ChestXray14(datasets.GeneratorBasedBuilder):
                                         num_classes=len(_NAMES),
                                         names=_NAMES
                                      )
-                                 )
+                                 ),
                        }
                     )
 		    keys = ("image", "labels")
 
+		if self.config.name == "object-detection":
+                    features = datasets.Features(
+                       {
+                           "image_id": datasets.Value("string"),
+                           "patient_id": datasets.Value("int32"),
+                           "image": datasets.Image(),
+                           "width": datasets.Value("int32"),
+                           "height": datasets.Value("int32"),
+                       }
+                     object_dict = {
+                         "image_id": datasets.Value("string"),
+                         "area": datasets.Value("int64"),
+                         "bbox": datasets.Sequence(datasets.Value("float32"), length=4),
+                     }
+                     features["objects"] = [object_dict]
+                     keys = ("image", "objects")
+
 		return datasets.DatasetInfo(
 		    description=_DESCRIPTION,
 		    features=features,