imageinwords.py

import datasets
import json
import pandas as pd
import string

_DESCRIPTION = """
ImageInWords (IIW), a carefully designed human-in-the-loop annotation framework for curating hyper-detailed image descriptions and a new dataset resulting from this process.
We validate the framework through evaluations focused on the quality of the dataset and its utility for fine-tuning with considerations for readability, comprehensiveness, specificity, hallucinations, and human-likeness.
"""

_HOMEPAGE = "https://google.github.io/imageinwords/"

_LICENSE = "CC BY 4.0"


_DATASET_GITHUB_PREFIX = "https://github.com/google/imageinwords/raw/main/datasets"

_DATASET_GITHUB_URLS = {
    "IIW-400": f"{_DATASET_GITHUB_PREFIX}/IIW-400/data.jsonl",
    "DCI_Test": f"{_DATASET_GITHUB_PREFIX}/DCI_Test/data.jsonl",
    "DOCCI_Test": f"{_DATASET_GITHUB_PREFIX}/DOCCI_Test/data.jsonl",
    "CM_3600": f"{_DATASET_GITHUB_PREFIX}/CM_3600/data.jsonl",
    "LocNar_Eval": f"{_DATASET_GITHUB_PREFIX}/LocNar_Eval/data.jsonl",
}

_DATASET_FEATURES = {
    "IIW-400": datasets.Features({
        "image/key": datasets.Value('string'),
        "image/url": datasets.Value('string'),
        "IIW": datasets.Value('string'),
        "IIW-P5B": datasets.Value('string'),
        "iiw-human-sxs-gpt4v": {
            "metrics/Comprehensiveness": datasets.Value('string'),
            "metrics/Specificity": datasets.Value('string'),
            "metrics/Hallucination": datasets.Value('string'),
            "metrics/First few line(s) as tldr": datasets.Value('string'),
            "metrics/Human Like": datasets.Value('string'),
        },
        "iiw-human-sxs-iiw-p5b": {
            "metrics/Comprehensiveness": datasets.Value('string'),
            "metrics/Specificity": datasets.Value('string'),
            "metrics/Hallucination": datasets.Value('string'),
            "metrics/First few line(s) as tldr": datasets.Value('string'),
            "metrics/Human Like": datasets.Value('string'),
        },
    }),
    "DCI_Test": datasets.Features({
        "image": datasets.Value('string'),
        "ex_id": datasets.Value('string'),
        "IIW": datasets.Value('string'),
        "metrics/Comprehensiveness": datasets.Value('string'),
        "metrics/Specificity": datasets.Value('string'),
        "metrics/Hallucination": datasets.Value('string'),
        "metrics/First few line(s) as tldr": datasets.Value('string'),
        "metrics/Human Like": datasets.Value('string'),
    }),
    "DOCCI_Test": datasets.Features({
        "image": datasets.Value('string'),
        "image/thumbnail_url": datasets.Value('string'),
        "IIW": datasets.Value('string'),
        "DOCCI": datasets.Value('string'),
        "metrics/Comprehensiveness": datasets.Value('string'),
        "metrics/Specificity": datasets.Value('string'),
        "metrics/Hallucination": datasets.Value('string'),
        "metrics/First few line(s) as tldr": datasets.Value('string'),
        "metrics/Human Like": datasets.Value('string'),
    }),
    "CM_3600": datasets.Features({
        "image/key": datasets.Value('string'),
        "image/url": datasets.Value('string'),
        "IIW-P5B": datasets.Value('string'),
    }),
    "LocNar_Eval": datasets.Features({
        "image/key": datasets.Value('string'),
        "image/url": datasets.Value('string'),
        "IIW-P5B": datasets.Value('string'),
    }),
}


_CM_3600_URL_PATTERN = string.Template("https://open-images-dataset.s3.amazonaws.com/crossmodal-3600/$IMAGE_KEY.jpg")
_DOCCI_AAR_URL_PATTERN = string.Template("https://storage.googleapis.com/docci/data/images_aar/$IMAGE_KEY.jpg")
_DOCCI_THUMBNAIL_URL_PATTERN = string.Template("https://storage.googleapis.com/docci/thumbnails/$IMAGE_KEY.jpg")
_LOCNAR_VALIDATION_URL_PATTERN = string.Template("https://open-images-dataset.s3.amazonaws.com/validation/$IMAGE_KEY.jpg")


class ImageInWords(datasets.GeneratorBasedBuilder):
    """ImageInWords dataset"""
    
    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="IIW-400", version=VERSION, description="IIW-400"),
        datasets.BuilderConfig(name="DCI_Test", version=VERSION, description="DCI_Test"),
        datasets.BuilderConfig(name="DOCCI_Test", version=VERSION, description="DOCCI_Test"),
        datasets.BuilderConfig(name="CM_3600", version=VERSION, description="CM_3600"),
        datasets.BuilderConfig(name="LocNar_Eval", version=VERSION, description="LocNar_Eval"),
    ]

    DEFAULT_CONFIG_NAME = "IIW-400"

    def _info(self):
        return datasets.DatasetInfo(
            features=_DATASET_FEATURES[self.config.name],
            homepage=_HOMEPAGE,
            description=_DESCRIPTION,
            license=_LICENSE,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        hf_auth_token = dl_manager.download_config.use_auth_token
        if hf_auth_token is None:
            raise ConnectionError(
                "Please set use_auth_token=True or use_auth_token='<TOKEN>' to download this dataset"
            )
    
        downloaded_file = dl_manager.download_and_extract(_DATASET_GITHUB_URLS[self.config.name])
        if self.config.name == "LocNar_Eval":
            split_type = datasets.Split.VALIDATION
        else:
            split_type = datasets.Split.TEST
        return [
            datasets.SplitGenerator(name=split_type, gen_kwargs={"filepath": downloaded_file}),
        ]

    def _generate_examples(self, filepath):
        match self.config.name:
            case "IIW-400":
                return self._generate_examples_iiw_400(filepath)
            case "DCI_Test":
                return self._generate_examples_dci_test(filepath)
            case "DOCCI_Test":
                return self._generate_examples_docci_test(filepath)
            case "CM_3600":
                return self._generate_examples_cm_3600(filepath)
            case "LocNar_Eval":
                return self._generate_examples_locnar_eval(filepath)

    def _generate_examples_iiw_400(self, filepath):
        with open(filepath) as fp:
            for json_line in fp:
                json_obj = json.loads(json_line.strip())
                json_obj["image/url"] = _DOCCI_AAR_URL_PATTERN.substitute(IMAGE_KEY=json_obj["image/key"])
                yield json_obj["image/key"], json_obj

    def _generate_examples_dci_test(self, filepath):
        with open(filepath) as fp:
            for json_line in fp:
                json_obj = json.loads(json_line.strip())
                yield json_obj["image"], json_obj

    def _generate_examples_docci_test(self, filepath):
        with open(filepath) as fp:
            for json_line in fp:
                json_obj = json.loads(json_line.strip())
                json_obj["image/thumbnail_url"] = _DOCCI_THUMBNAIL_URL_PATTERN.substitute(IMAGE_KEY=json_obj["image"])
                yield json_obj["image"], json_obj

    def _generate_examples_cm_3600(self, filepath):
        with open(filepath) as fp:
            for json_line in fp:
                json_obj = json.loads(json_line.strip())
                json_obj["image/url"] = _CM_3600_URL_PATTERN.substitute(IMAGE_KEY=json_obj["image/key"])
                del json_obj["image/source"]
                yield json_obj["image/key"], json_obj
                
            
    def _generate_examples_locnar_eval(self, filepath):
        with open(filepath) as fp:
            for json_line in fp:
                json_obj = json.loads(json_line.strip())
                json_obj["image/url"] = _LOCNAR_VALIDATION_URL_PATTERN.substitute(IMAGE_KEY=json_obj["image/key"])
                del json_obj["image/source"]
                yield json_obj["image/key"], json_obj