feat: Add splits to train val test

dataset_infos.json

@@ -1 +1 @@
-{"default": {"description": "", "citation": "", "homepage": "", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "school_notebooks_en", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 15374, "num_examples": 90, "dataset_name": "school_notebooks_en"}}, "download_checksums": {"images.zip": {"num_bytes": 356400252, "checksum": "295ab37246a1ec976f50019ab77b3bb35543b0cdcbd2b825a7949c4959448a75"}}, "download_size": 356400252, "post_processing_size": null, "dataset_size": 15374, "size_in_bytes": 356415626}}
+{"default": {"description": "", "citation": "", "homepage": "", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "school_notebooks_en", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 11957, "num_examples": 70, "dataset_name": "school_notebooks_en"}, "test": {"name": "test", "num_bytes": 1692, "num_examples": 10, "dataset_name": "school_notebooks_en"}, "validation": {"name": "validation", "num_bytes": 1726, "num_examples": 10, "dataset_name": "school_notebooks_en"}}, "download_checksums": {"images.zip": {"num_bytes": 356400252, "checksum": "295ab37246a1ec976f50019ab77b3bb35543b0cdcbd2b825a7949c4959448a75"}, "annotations_train.json": {"num_bytes": 8644229, "checksum": "2b52b1876e47c6970e2ba97f57fe2a431a2bca0c5b9450360c4bf481643c0b5f"}, "annotations_test.json": {"num_bytes": 687288, "checksum": "c241e966d26d10cd7fa19730489cac104ebebfd9931d0acd0c4fb7369a958672"}, "annotations_val.json": {"num_bytes": 1768738, "checksum": "8a6b80a2c73ca25a2b2b23d4620c4c34492b728ed094a824e82f49427712c271"}}, "download_size": 367500507, "post_processing_size": null, "dataset_size": 15375, "size_in_bytes": 367515882}}

school_notebooks_EN.py

@@ -1,4 +1,5 @@
 import os
+import json
 import datasets
 
 
@@ -13,24 +14,50 @@ class SchoolNotebooks(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        DL_URLS = [
-            "images.zip"
-        ]
-        data_files = dl_manager.download_and_extract(DL_URLS)
+        _URLS = {
+            "images": "images.zip",
+            "train_data": "annotations_train.json",
+            "test_data": "annotations_test.json",
+            "val_data": "annotations_val.json"
+        }
+        data_files = dl_manager.download_and_extract(_URLS)
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "image_paths": dl_manager.iter_files(data_files),
+                    "image_paths": dl_manager.iter_files(data_files["images"]),
+                    "annotation_path": data_files["train_data"],
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "image_paths": dl_manager.iter_files(data_files["images"]),
+                    "annotation_path": data_files["test_data"],
                 },
             ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "image_paths": dl_manager.iter_files(data_files["images"]),
+                    "annotation_path": data_files["val_data"],
+                },
+            )
         ]
 
-    def _generate_examples(self, image_paths):
+    def _generate_examples(self, image_paths, annotation_path):
         """Generate examples."""
+        with open(annotation_path, 'r') as f:
+            data = json.load(f)
+
+        image_names = set()
+        for image_data in data['images']:
+            image_names.add(image_data['file_name'])
+
         for idx, image_path in enumerate(image_paths):
-            example = {
-                "image": image_path,
-            }
-            yield idx, example
+            if os.path.basename(image_path) in image_names:
+                example = {
+                    "image": image_path,
+                }
+                yield idx, example