Update mhr_recognize_datasets.py

mhr_recognize_datasets.py

@@ -51,25 +51,28 @@ class MHRRecognizeDatasets(datasets.GeneratorBasedBuilder):
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
         download_files = dl_manager.download_and_extract(_DATA_URL)
-        print(download_files)
+        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)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "image_path": os.path.join(download_files[self.config.name+"_image"]),
-                    "label_path": os.path.join(download_files[self.config.name+"_label"]),
+                    "images": images,
+                    "label": label,
                 },
             )
         ]
         
-    def _generate_examples(self, image_path, label_path):
-        print("1:", image_path, label_path)
+    def _generate_examples(self, images, label):
+        print("1:", images, label_path)
         if True:
         # if self.config.name == "whole":
         # Read csv with image labels
-            label_csv = pd.read_csv(label_path)
+            label_csv = pd.read_csv(label)
             print("2:", label_csv)
-            for i, path in enumerate(image_path):
+            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