Upload mscoco_jsonl_full.py

mscoco_jsonl_full.py

@@ -0,0 +1,61 @@
+import datasets
+import pickle
+import json
+
+class EmbeddingsDatasetConfig(datasets.BuilderConfig):
+
+    def __init__(self, image_base_m, embeddingSize, **kwargs):
+        super(EmbeddingsDatasetConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
+        self.data_urls = ""
+        self.image_base_m = image_base_m
+        self.embeddingSize = embeddingSize
+
+
+class ImageCaptionsEmbeddings(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        EmbeddingsDatasetConfig(
+            name="Vit-B-32",
+            image_base_m="Vit-B-32-2",
+            embeddingSize=512,
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "Vit-B-32"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description='test',
+            features=datasets.Features(
+                {
+                    "id": datasets.Value('string'),
+                    "embedding": datasets.Array2D((1, self.config.embeddingSize), 'float32')
+                }
+            ),
+        )
+
+    def _split_generators(self, dl_manager):
+
+        urls_to_download = self.config.data_urls
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        downloaded_files = ["/home/think3/Desktop/1. MSCOCO_captions_dataset_edited/dataset_test_jsonl/en_captions_json.jsonl"]
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN,
+                                    gen_kwargs={
+                                        "data_files": downloaded_files,
+                                    })
+        ]
+
+    def _generate_examples(self, data_files):
+
+        for data_file in data_files:
+            
+            with open(data_file, "r") as input_file:
+                for line in input_file:
+
+                    json_data = json.loads(line)
+
+                    yield json_data["id"], {
+                        "id": json_data["id"],
+                        "embedding": json_data["embedding"],
+                    }