| import csv | |
| import json | |
| import os | |
| from PIL import Image | |
| import pandas as pd | |
| from huggingface_hub import hf_hub_download, snapshot_download | |
| import datasets | |
| import cv2 | |
| # _CITATION = """\ | |
| # @InProceedings{huggingface:dataset, | |
| # title = {A great new dataset}, | |
| # author={huggingface, Inc. | |
| # }, | |
| # year={2020} | |
| # } | |
| # """ | |
| _DESCRIPTION = """\ | |
| Image Quality Assessment Dataset consisting of 25 reference images, 17 different distortions and 4 intensities per distortion. | |
| In total there are 1700 (reference, distortion, MOS) tuples. | |
| """ | |
| # _HOMEPAGE = "" | |
| # _LICENSE = "" | |
| # TODO: Add link to the official dataset URLs here | |
| # The HuggingFace Datasets library doesn't host the datasets but only points to the original files. | |
| # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
| # _URLS = { | |
| # "first_domain": "https://huggingface.co/great-new-dataset-first_domain.zip", | |
| # "second_domain": "https://huggingface.co/great-new-dataset-second_domain.zip", | |
| # } | |
| # _REPO = "https://huggingface.co/datasets/frgfm/imagenette/resolve/main/metadata" # Stolen from imagenette.py | |
| _REPO = "https://huggingface.co/datasets/Jorgvt/TID2008/resolve/main" | |
| class TID2008(datasets.GeneratorBasedBuilder): | |
| """TID2008 Image Quality Dataset""" | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset | |
| features = datasets.Features( | |
| { | |
| "reference": datasets.Image(), | |
| "distorted": datasets.Image(), | |
| "mos": datasets.Value("float") | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| # supervised_keys=("reference", "distorted", "mos"), | |
| # homepage=_HOMEPAGE, | |
| # license=_LICENSE, | |
| # citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data_path = dl_manager.download("image_pairs_mos.csv") | |
| data = pd.read_csv(data_path, index_col=0) | |
| # kk = dl_manager.download("distorted_images") | |
| # print(kk) | |
| root_path = "/".join(data_path.split("/")[:-1]) | |
| # reference_path = dl_manager.download("reference_images") | |
| # distorted_path = dl_manager.download("distorted_images") | |
| reference_paths = data["Reference"].apply(lambda x: os.path.join("reference_images", x)).to_list() | |
| distorted_paths = data["Distorted"].apply(lambda x: os.path.join("distorted_images", x)).to_list() | |
| reference_paths = dl_manager.download(reference_paths) | |
| distorted_paths = dl_manager.download(distorted_paths) | |
| # dl_manager.download(data["Reference"]) | |
| # data["Reference"] = data["Reference"].apply(lambda x: os.path.join(reference_path, x)) | |
| # data["Distorted"] = data["Distorted"].apply(lambda x: os.path.join(distorted_path, x)) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| # "reference": data["Reference"], | |
| # "distorted": data["Distorted"], | |
| "reference": reference_paths, | |
| "distorted": distorted_paths, | |
| "mos": data["MOS"], | |
| "split": "train", | |
| }, | |
| ) | |
| ] | |
| # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
| def _generate_examples(self, reference, distorted, mos, split): | |
| for key, (ref, dist, m) in enumerate(zip(reference, distorted, mos)): | |
| yield key, { | |
| "reference": ref, | |
| "distorted": dist, | |
| "mos": m, | |
| } | |
| # with open(filepath, encoding="utf-8") as f: | |
| # for key, row in enumerate(f): | |
| # data = json.loads(row) | |
| # if self.config.name == "first_domain": | |
| # # Yields examples as (key, example) tuples | |
| # yield key, { | |
| # "sentence": data["sentence"], | |
| # "option1": data["option1"], | |
| # "answer": "" if split == "test" else data["answer"], | |
| # } | |
| # else: | |
| # yield key, { | |
| # "sentence": data["sentence"], | |
| # "option2": data["option2"], | |
| # "second_domain_answer": "" if split == "test" else data["second_domain_answer"], | |
| # } |