update

README.md

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+---
+annotations_creators: []
+language:
+- en
+language_creators: []
+license:
+- other
+multilinguality: []
+pretty_name: This is a test version for ELEVATER benchmark.
+size_categories:
+- 10M<n<100M
+source_datasets:
+- original
+tags: []
+task_categories:
+- image-classification
+- object-detection
+task_ids:
+- multi-class-image-classification
+---
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:**
+- **Repository:**
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.

zhlds.py

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+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""The ELEVATER benchmark"""
+
+import json
+import os
+
+import datasets
+
+from zipfile import ZipFile
+from io import BytesIO
+from PIL import Image
+
+_ELEVATER_CITATION = """\
+@article{li2022elevater,
+    title={ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models},
+    author={Li, Chunyuan and Liu, Haotian and Li, Liunian Harold and Zhang, Pengchuan and Aneja, Jyoti and Yang, Jianwei and Jin, Ping and Lee, Yong Jae and Hu, Houdong and Liu, Zicheng and Gao, Jianfeng},
+    journal={Neural Information Processing Systems},
+    year={2022}
+}
+
+Note that each ELEVATER dataset has its own citation. Please see the source to
+get the correct citation for each contained dataset.
+"""
+
+_CIFAR_10_DESCRIPTION="""\
+The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images."""
+
+_CIFAR_10_CITATION="""\
+@article{krizhevsky2009learning,
+  title={Learning multiple layers of features from tiny images},
+  author={Krizhevsky, Alex and Hinton, Geoffrey and others},
+  year={2009},
+  publisher={Toronto, ON, Canada}
+}"""
+
+class ELEVATERConfig(datasets.BuilderConfig):
+
+    """BuilderConfig for ELEVATER."""
+    print(f"zhlds/zhlds.py, line 50")
+    def __init__(self, name, description, contact, version, type_, root_folder, labelmap, num_classes, train, test, citation, url, **kwargs):
+        """BuilderConfig for ELEVATER.
+        Args:
+          features: `list[string]`, list of the features that will appear in the
+            feature dict. Should not include "label".
+          data_url: `string`, url to download the zip file from.
+          citation: `string`, citation for the data set.
+          url: `string`, url for information about the data set.
+          label_classes: `list[string]`, the list of classes for the label if the
+            label is present as a string. Non-string labels will be cast to either
+            'False' or 'True'.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(ELEVATERConfig, self).__init__(**kwargs)
+        self.name = name
+        self.description = description
+        self.contact = contact
+        self.version = version
+        self.type = type_
+        self.root_folder = root_folder
+        self.labelmap = labelmap
+        self.num_classes = num_classes
+        self.train = train
+        self.test = test
+        self.citation = citation
+        self.url = url
+
+
+class ELEVATER(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        ELEVATERConfig(
+            name="cifar-10",
+            description="The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.",
+            contact="pinjin",
+            version="1.0.0",
+            type_="classification_multiclass",
+            root_folder="classification/cifar_10_20211007",
+            labelmap="labels.txt",
+            num_classes=10,
+            train={
+                "index_path": "train.txt",
+                "files_for_local_usage": ["train.zip"],
+                "num_images": 50000
+            },
+            test={
+                "index_path": "test.txt",
+                "files_for_local_usage": ["val.zip"],
+                "num_images": 10000
+            },
+            citation=_CIFAR_10_CITATION,
+            url="https://cvinthewildeus.blob.core.windows.net/datasets/",
+        ),
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "image_file_path": datasets.Value("string"),
+                "image": datasets.Image(),
+                "labels": datasets.Value("int32")
+            }
+        )
+        return datasets.DatasetInfo(
+            description=self.config.description,
+            features=features,
+            citation=self.config.citation + '\n' + _ELEVATER_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        _URL = self.config.url + self.config.root_folder
+        urls_to_download = {
+            "labelmap": os.path.join(_URL, self.config.labelmap),
+            "train": {
+                "images": os.path.join(_URL, self.config.train['files_for_local_usage'][0]),
+                "index": os.path.join(_URL, self.config.train['index_path']),
+            },
+            "test": {
+                "images": os.path.join(_URL, self.config.test['files_for_local_usage'][0]),
+                "index": os.path.join(_URL, self.config.test['index_path']),
+            }
+        } 
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "images": downloaded_files["train"]["images"],
+                    "index": downloaded_files["train"]["index"],
+                    "split": datasets.Split.TRAIN,
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "images": downloaded_files["test"]["images"],
+                    "index": downloaded_files["test"]["index"],
+                    "split": datasets.Split.TEST,
+                },
+            )
+        ]
+
+    def _generate_examples(self, images, index, split):
+        image_path_label_list = []
+        with open(index, "r") as f:
+            lines = f.readlines()
+            for i, line in enumerate(lines):
+                line_split = line[:-1].split(" ")
+                label = int(line_split[1])
+                image_path = line_split[0].split('@')[1]
+                path = images + '/' + image_path
+                yield i, {
+                    "image_file_path": path,
+                    "image": path,
+                    "labels": label,
+                }