import collections
import json
import os
import datasets

ANNOTATION_FILENAME = "_annotations.coco.json"

class StorageBuilderConfig(datasets.BuilderConfig):
    def __init__(self, data_urls, **kwargs):
        super(StorageBuilderConfig, self).__init__(**kwargs)
        self.data_urls = data_urls

class StorageBuilder(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        StorageBuilderConfig(name="storage_builder", data_urls={"train": "./storage_builder/data/train"}),
    ]

    def _info(self):
        features = datasets.Features(
            {
                "image_id": datasets.Value("int64"), 
                "image": datasets.Image(), 
                "width": datasets.Value("int32"), 
                "height": datasets.Value("int32"), 
                "objects": datasets.Sequence(
                    {
                        "id": datasets.Value("int64"), 
                        "area": datasets.Value("int64"), 
                        "bbox": datasets.Sequence(datasets.Value("float32"), length=4), 
                        "category": datasets.Value("string")
                    }
                )
            }
        )
        
        return datasets.DatasetInfo(features=features)

    def _split_generators(self, dl_manager):
        print(self.config.data_urls)
        # data_files = dl_manager.download_and_extract(self.config.data_urls)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"folder_dir": self.config.data_urls["train"]})
            # datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"folder_dir": data_files["validation"]}), 
            # datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"folder_dir": data_files["test"]})
        ]

    def _generate_examples(self, folder_dir):
        def process_annot(annot, category_id_to_category):
            return {"id": annot["id"], "area": annot["area"], "bbox": annot["bbox"], "category": annot["category_id"]}

        image_id_to_image = {}
        idx = 0

        annotation_filepath = os.path.join(folder_dir, ANNOTATION_FILENAME)
        with open(annotation_filepath, "r") as f:
            annotations = json.load(f)
        category_id_to_category = {category["id"]: category["name"] for category in annotations["categories"]}
        
        image_id_to_annotations = collections.defaultdict(list)
        for annot in annotations["annotations"]:
            image_id_to_annotations[annot["image_id"]].append(annot)
        filename_to_image = {image["file_name"]: image for image in annotations["images"]}

        for filename in os.listdir(folder_dir):
            filepath = os.path.join(folder_dir, filename)
            if filename in filename_to_image:
                image = filename_to_image[filename]
                with open(filepath, "rb") as f:
                    image_bytes = f.read()
                objects = [process_annot(annot, category_id_to_category) for annot in image_id_to_annotations[image["id"]]]
                yield idx, {"image_id": image["id"], "image": {"path": filepath, "bytes": image_bytes}, "height": image["height"], "width": image["width"], "objects": objects}
                idx += 1