Update script to hub

Boat_dataset.py

@@ -1,3 +1,4 @@
+# Source: https://github.com/huggingface/datasets/blob/main/templates/new_dataset_script.py
 # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
@@ -48,7 +49,7 @@ _LICENSE = ""
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _URLS = {
-    "Boat_dataset": "ftp://arg.lab.nycu.edu.tw/arg-projectfile-download/detr/dataset/Boat_dataset.zip",
+    "Boat_dataset": "ftp://arg.lab.nycu.edu.tw/arg-projectfile-download/detr/dataset/annotations.zip",
 }
 
 
@@ -82,7 +83,7 @@ class BoatDataset(datasets.GeneratorBasedBuilder):
         features=datasets.Features({
             'image_id': datasets.Value('int32'),
             # 'image': datasets.Image(), # This is commented out because you can't directly store PIL images in the dataset.
-            'file_name': datasets.Value('string'),  # Store the path to the image file instead.
+            'image_path': datasets.Value('string'),  # Store the path to the image file instead.
             'width': datasets.Value('int32'),
             'height': datasets.Value('int32'),
             'objects': datasets.Features({
@@ -92,8 +93,6 @@ class BoatDataset(datasets.GeneratorBasedBuilder):
                 'category': datasets.Sequence(datasets.Value('int32'))
             }),
         })
-
-        print(features)
         
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
@@ -120,7 +119,6 @@ class BoatDataset(datasets.GeneratorBasedBuilder):
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         urls = _URLS[self.config.name]
         data_dir = dl_manager.download_and_extract(urls)
-        data_dir = os.path.join(data_dir, "images")
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -146,14 +144,6 @@ class BoatDataset(datasets.GeneratorBasedBuilder):
                     "split": "val_real",
                 },
             ),
-            # datasets.SplitGenerator(
-            #     name=datasets.Split.TEST,
-            #     # These kwargs will be passed to _generate_examples
-            #     gen_kwargs={
-            #         "filepath": os.path.join(data_dir, "test.jsonl"),
-            #         "split": "test"
-            #     },
-            # ),
         ]
 
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
@@ -165,7 +155,7 @@ class BoatDataset(datasets.GeneratorBasedBuilder):
                     # Proceed to use 'data' for generating examples
                     yield key, {
                         "image_id": data["image_id"],
-                        "file_name": data["file_name"],
+                        "image_path": data["image_path"],
                         "width": data["width"],
                         "height": data["height"],
                         "objects": data["objects"],
@@ -173,30 +163,3 @@ class BoatDataset(datasets.GeneratorBasedBuilder):
                 except json.JSONDecodeError:
                     print(f"Skipping invalid JSON at line {key + 1}: {row}")
                     continue
-
-    # def _generate_examples(self, filepath, split):
-    #     # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-    #     # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-    #     with open(filepath, encoding="utf-8") as f:
-    #         for key, row in enumerate(f, 1):  # Start enumeration at 1 for line numbers
-    #             try:
-    #                 data = json.loads(row)
-    #                 # Your existing processing logic here
-    #             except json.JSONDecodeError:
-    #                 print(f"Skipping invalid JSON at line {key}")
-    #                 continue
-    #             # for key, row in enumerate(f):
-    #             #     data = json.loads(row)
-
-    #             yield key, {
-    #                 "image_id": data["image_id"],
-    #                 "file_name": data["file_name"],
-    #                 "width": data["width"],
-    #                 "height": data["height"],
-    #                 "objects": {
-    #                     "id": data["objects"]["id"],
-    #                     "area": data["objects"]["area"],
-    #                     "bbox": data["objects"]["bbox"],
-    #                     "category": data["objects"]["category"],
-    #                 },
-    #             }