update dataset with task1

skin-lesion.py

@@ -60,7 +60,8 @@ _URLS = {
     "milia_like_cyst": "https://storage.googleapis.com/lesion-dataset/dataset-milia_like_cyst.zip",
     "negative_network": "https://storage.googleapis.com/lesion-dataset/dataset-negative_network.zip",
     "pigment_network": "https://storage.googleapis.com/lesion-dataset/dataset-pigment_network.zip",
-    "streaks": "https://storage.googleapis.com/lesion-dataset/dataset-streaks.zip"
+    "streaks": "https://storage.googleapis.com/lesion-dataset/dataset-streaks.zip",
+    "task1": "https://storage.googleapis.com/lesion-dataset/dataset-task1.zip",
 }
 
 
@@ -76,9 +77,10 @@ class LesionDataset(datasets.GeneratorBasedBuilder):
         datasets.BuilderConfig(name="milia_like_cyst", version=VERSION, description="This will return the dataset with only milia_like_cyst class"),
         datasets.BuilderConfig(name="negative_network", version=VERSION, description="This will return the dataset with only negative_network class"),
         datasets.BuilderConfig(name="pigment_network", version=VERSION, description="This will return the dataset with only pigment_network class"),
-        datasets.BuilderConfig(name="streaks", version=VERSION, description="This will return the dataset with only streaks class")
+        datasets.BuilderConfig(name="streaks", version=VERSION, description="This will return the dataset with only streaks class"),
+        datasets.BuilderConfig(name="task1", version=VERSION, description="This will return the dataset for task1"),
     ]
-    DEFAULT_CONFIG_NAME = "full"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    DEFAULT_CONFIG_NAME = "task1"  # It's not mandatory to have a default configuration. Just use one if it make sense.
 
     def _info(self):
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
@@ -93,8 +95,8 @@ class LesionDataset(datasets.GeneratorBasedBuilder):
                     "label4": datasets.Image(),
                 }
             )
-            print(type(features))
-        elif self.config.name in ['globules', 'milia_like_cyst', 'negative_network', 'pigment_network', 'streaks']:
+
+        elif self.config.name in ['globules', 'milia_like_cyst', 'negative_network', 'pigment_network', 'streaks', 'task1']:
             features = datasets.Features(
                 {
                     "image": datasets.Image(),
@@ -144,13 +146,45 @@ class LesionDataset(datasets.GeneratorBasedBuilder):
             'streaks': 4
         }
 
+        # Task 2
+        if self.config.name in ['full', 'globules', 'milia_like_cyst', 'negative_network', 'pigment_network', 'streaks']:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1-2_Training_Input"),
+                        "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task2_Training_GroundTruth_v3"),
+                        "split": "train",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1-2_Validation_Input"),
+                        "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task2_Validation_GroundTruth"),
+                        "split": "validation",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1-2_Test_Input"),
+                        "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task2_Test_GroundTruth"),
+                        "split": "test"
+                    },
+                ),
+            ]
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "filepath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1-2_Training_Input"),
-                    "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task2_Training_GroundTruth_v3"),
+                    "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1_Training_GroundTruth"),
                     "split": "train",
                 },
             ),
@@ -159,7 +193,7 @@ class LesionDataset(datasets.GeneratorBasedBuilder):
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "filepath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1-2_Validation_Input"),
-                    "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task2_Validation_GroundTruth"),
+                    "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1_Validation_GroundTruth"),
                     "split": "validation",
                 },
             ),
@@ -168,7 +202,7 @@ class LesionDataset(datasets.GeneratorBasedBuilder):
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "filepath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1-2_Test_Input"),
-                    "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task2_Test_GroundTruth"),
+                    "labelpath": os.path.join(data_dir, f"{base_name}/ISIC2018_Task1_Test_GroundTruth"),
                     "split": "test"
                 },
             ),