Update mhr_recognize_datasets.py

mhr_recognize_datasets.py

@@ -10,7 +10,6 @@ _DESCRIPTION = """\
 Monster Hunter Rise images and labels.
 """
 
-
 _DATA_URL = {
     "whole_image": "https://huggingface.co/datasets/miojizzy/mhr_recognize_datasets/resolve/main/data/whole/train.zip",
     "whole_label": "https://huggingface.co/datasets/miojizzy/mhr_recognize_datasets/resolve/main/data/whole/label.csv",
@@ -23,15 +22,14 @@ _DATA_URL = {
 class MHRRecognizeDatasetsConfig(datasets.BuilderConfig):
     def __init__(self, name, **kwargs):
         super(MHRRecognizeDatasetsConfig, self).__init__(
-		version=datasets.Version("1.0.0"),
-		name=name,
-		description=_DESCRIPTION,
-		**kwargs,
+        	version=datasets.Version("1.0.0"),
+        	name=name,
+        	description=_DESCRIPTION,
+        	**kwargs,
 	    )
 
 class MHRRecognizeDatasets(datasets.GeneratorBasedBuilder):
-    DEFAULT_WRITER_BATCH_SIZE = 8
-    
+
     BUILDER_CONFIGS = [
         MHRRecognizeDatasetsConfig("whole"),
         MHRRecognizeDatasetsConfig("hole"),
@@ -40,46 +38,28 @@ class MHRRecognizeDatasets(datasets.GeneratorBasedBuilder):
 
     def _info(self):
         features = datasets.Features({
-                    "image": datasets.Image(),
-                    "label": datasets.Value("int32"),
-                })
+            "image": datasets.Image(),
+            "label": datasets.Value("int32"),
+        })
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=features
         )
 
     def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
         download_files = dl_manager.download_and_extract(_DATA_URL)
-        name = self.config.name
-        images = dl_manager.iter_files(os.path.join(download_files[name+"_image"]))
-        label = os.path.join(download_files[name+"_label"])
-        print(download_files, images, label)
+        images = dl_manager.iter_files(os.path.join(download_files[self.config.name+"_image"]))
+        label = os.path.join(download_files[self.config.name+"_label"])
         return [
             datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "images": images,
-                    "label": label,
-                },
+                name = datasets.Split.TRAIN,
+                gen_kwargs = {"images": images, "label": label},
             )
         ]
         
     def _generate_examples(self, images, label):
-        #print("1:", images, label)
-        if True:
-        # if self.config.name == "whole":
-        # Read csv with image labels
-            label_csv = pd.read_csv(label)
-            label_csv = label_csv.fillna(-1)
-            #print("2:", label_csv)
-            for i, path in enumerate(images):
-                file_name = os.path.basename(path)
-                #print("3:", i, path, file_name)
-                # Get image id to filter the respective row of the csv
-                image_label = label_csv[label_csv["name"] == file_name]['label'].values[0]
-                #print("5:", type(image_label), image_label)
-                yield i, { 
-                    "image": path, 
-                    "label": image_label, 
-                }
+        label_csv = pd.read_csv(label).fillna(-1)
+        for i, path in enumerate(images):
+            file_name = os.path.basename(path)
+            image_label = label_csv[label_csv["name"] == file_name]['label'].values[0]
+            yield i, {"image": path, "label": image_label}