Add _generate_example for image-segmentation

rock-glacier-dataset.py

@@ -14,6 +14,7 @@
 """Rock Glacier dataset with images of the chilean andes."""
 
 import os
+import re
 
 import datasets
 from datasets.tasks import ImageClassification
@@ -35,11 +36,11 @@ _DESCRIPTION = """\
 TODO: Add a description...
 """
 
-_MASKS_URLS = ["https://huggingface.co/datasets/alkzar90/rock-glacier-dataset/resolve/main/data/glaciar_masks_trainset.zip"]
 
 _URLS = {
 	"train": "https://huggingface.co/datasets/alkzar90/rock-glacier-dataset/resolve/main/data/train.zip",
-	"validation": "https://huggingface.co/datasets/alkzar90/rock-glacier-dataset/resolve/main/data/validation.zip"
+	"validation": "https://huggingface.co/datasets/alkzar90/rock-glacier-dataset/resolve/main/data/validation.zip",
+	"train_mask": "https://huggingface.co/datasets/alkzar90/rock-glacier-dataset/resolve/main/data/glaciar_masks_trainset.zip",
 }
 
 _NAMES = ["glaciar", "cordillera"]
@@ -90,22 +91,38 @@ class RockGlacierDataset(datasets.GeneratorBasedBuilder):
 
    def _split_generators(self, dl_manager):
        data_files = dl_manager.download_and_extract(_URLS)
-       return [
-	   datasets.SplitGenerator(
-	       name=datasets.Split.TRAIN,
-	       gen_kwargs={
-		   "files": dl_manager.iter_files([data_files["train"]]),
-	       },
-	   ),
-	   datasets.SplitGenerator(
-	       name=datasets.Split.VALIDATION,
-	       gen_kwargs={
-		   "files": dl_manager.iter_files([data_files["validation"]]),
-	       },
- 	   ),
-       ]
+       
+       if self.config.name == "image-classification":
+          return [
+	          datasets.SplitGenerator(
+	          name=datasets.Split.TRAIN,
+	          gen_kwargs={
+		          "files": dl_manager.iter_files([data_files["train"]]),
+		          "split": "training",
+	          },
+	          ),
+	          datasets.SplitGenerator(
+	          name=datasets.Split.VALIDATION,
+	          gen_kwargs={
+		          "files": dl_manager.iter_files([data_files["validation"]]),
+		          "split": "validation",
+	          },
+ 	         ),
+           ]
+           
+       if self.config.name == "image-segmentation":
+          train_data = dl_manager.iter_files(data_files["train"]), dl_manager.iter_files(data_files["train_mask"])
+          return [
+             datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                   "files": train_data,
+                   "split": "training",
+                },
+             )]
+                
 
-   def _generate_examples(self, files):
+   def _generate_examples(self, files, split):
    
       if self.config.name == "image-classification":
          for i, path in enumerate(files):
@@ -115,4 +132,20 @@ class RockGlacierDataset(datasets.GeneratorBasedBuilder):
                   "image": path,
                   "labels": os.path.basename(os.path.dirname(path)).lower(),
                   }
+      
+      if self.config.name == "image-segmentation":
+         if split == "training":
+            images, masks = files
+            imageId2mask = {}
+            # iterate trought masks
+            for mask_path in masks:
+               mask_id = re.search('\d+', mask_path).group(0)
+               imageId2mask[mask_id] = mask_path     
+            for i, path in enumerate(files):
+               file_name = os.path.basename(path)
+               if file_name.endswith(".png"):
+                  yield i, {
+                     "image": path,
+                     "labels": imageId2mask[re.search('\d+', file_name).group(0)]
+                  }