mini_car_bikes_detection.py

from PIL import Image
import numpy as np

import json
import os

import datasets


_DESCRIPTION = """
"""

_HOMEPAGE = ""

_LICENSE = ""

_URL = "https://huggingface.co/datasets/alexrods/mini_car_bikes_detection/resolve/main"

_URLS = {
    "train_images": f"{_URL}/data/train.zip",
    "test_images": f"{_URL}/data/test.zip",
}

_CATEGORIES = ['Car', 'bike']


class MiniCarBikesDetection(datasets.GeneratorBasedBuilder):

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        features = datasets.Features(
            {
                "image": datasets.Image(),
                "image_name": datasets.Value("string"),
            }
        )
       
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
        )


    def _split_generators(self, dl_manager):
            data_files = dl_manager.download(_URLS)
            return [
                datasets.SplitGenerator(
                    name=datasets.Split.TRAIN,
                    gen_kwargs={
                        "image_files": dl_manager.iter_archive(data_files["train_images"]),
                    },
                ),
                datasets.SplitGenerator(
                    name=datasets.Split.TEST,
                    gen_kwargs={
                        "image_files": dl_manager.iter_archive(data_files["test_images"]),
                    },
                ),
            ]
        
    def _generate_examples(self, image_files): 
        for image_file in image_files:
            image_name = image_file[0].split("/")[1]
            yield  image_file, {
                "image": {"path": image_file[0], "bytes": image_file[1].read()},
                "image_name": image_name,
            }