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Browse files- README.md +0 -164
- data/annotations/test.jsonl +0 -0
- data/annotations/train.jsonl → default/hl-test.parquet +2 -2
- data/images.tar.gz → default/hl-train-00000-of-00004.parquet +2 -2
- default/hl-train-00001-of-00004.parquet +3 -0
- default/hl-train-00002-of-00004.parquet +3 -0
- default/hl-train-00003-of-00004.parquet +3 -0
- hl.py +0 -131
README.md
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---
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license: apache-2.0
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task_categories:
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- image-to-text
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- question-answering
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- zero-shot-classification
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language:
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- en
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multilinguality:
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- monolingual
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task_ids:
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- text-scoring
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pretty_name: HL (High-Level Dataset)
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size_categories:
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- 10K<n<100K
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annotations_creators:
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- crowdsurced
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annotations_origin:
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- crowdsurced
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dataset_info:
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features:
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- name: file_name
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dtype: string
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captions:
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- name: scene
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sequence:
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dtype: string
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- name: action
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sequence:
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dtype: string
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- name: rationale
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sequence:
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dtype: string
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- name: object
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sequence:
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dtype: string
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splits:
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- name: train
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num_examples: 13498
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- name: test
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num_examples: 1499
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---
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# Dataset Card for the High-Level Dataset
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks](#supported-tasks)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:**
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- **Repository:
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- **Paper:**
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- **Point of Contact:**
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### Dataset Summary
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[More Information Needed]
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### Supported Tasks
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### Languages
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English
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## Dataset Structure
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[More Information Needed]
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### Data Instances
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[More Information Needed]
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### Data Fields
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[More Information Needed]
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### Data Splits
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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[More Information Needed]
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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[More Information Needed]
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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```
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```
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data/annotations/test.jsonl
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The diff for this file is too large to render.
See raw diff
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data/annotations/train.jsonl → default/hl-test.parquet
RENAMED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:e9cac32227680d47f032fa1e2a055f402b5f03af7d2b3e3ce156b7286c0acbb3
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size 246309674
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data/images.tar.gz → default/hl-train-00000-of-00004.parquet
RENAMED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:eb34b158f7e9b5873b672ad632f7ed0f70b765c3234f04bbb567e4031f8e72e2
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size 659871158
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default/hl-train-00001-of-00004.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:1c3d45bd5513a347010c19e5bf3145c884791414235a08dfda693491a0fbf7e4
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size 650392195
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default/hl-train-00002-of-00004.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:8d4dffec44058aa74f1d38c68b461482d1fd7d7e4063e746e69c6363f431525e
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size 652455208
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default/hl-train-00003-of-00004.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:cc5eefba2d5a37a3f7757dff02024440820a2d25a3a1b2e60a64656b400a7129
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size 245980507
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hl.py
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# coding=utf-8
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""High-Level dataset."""
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import json
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from pathlib import Path
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import datasets
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_CITATION = """\
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@misc{}
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"""
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_DESCRIPTION = """\
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High-level Dataset
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"""
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# github link
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_HOMEPAGE = ""
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_LICENSE = "Apache 2.0"
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_IMG = "https://huggingface.co/datasets/michelecafagna26/hl/resolve/main/data/images.tar.gz"
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_TRAIN = "https://huggingface.co/datasets/michelecafagna26/hl/resolve/main/data/annotations/train.jsonl"
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_TEST = "https://huggingface.co/datasets/michelecafagna26/hl/resolve/main/data/annotations/test.jsonl"
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class HL(datasets.GeneratorBasedBuilder):
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"""High Level Dataset."""
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VERSION = datasets.Version("1.0.0")
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def _info(self):
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features = datasets.Features(
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{
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"file_name": datasets.Value("string"),
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"image": datasets.Image(),
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"scene": datasets.Sequence(datasets.Value("string")),
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"action": datasets.Sequence(datasets.Value("string")),
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"rationale": datasets.Sequence(datasets.Value("string")),
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"object": datasets.Sequence(datasets.Value("string")),
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# "captions": {
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# "scene": datasets.Sequence(datasets.Value("string")),
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# "action": datasets.Sequence(datasets.Value("string")),
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# "rationale": datasets.Sequence(datasets.Value("string")),
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# "object": datasets.Sequence(datasets.Value("string")),
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# },
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"confidence": {
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"scene": datasets.Sequence(datasets.Value("float32")),
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"action": datasets.Sequence(datasets.Value("float32")),
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"rationale": datasets.Sequence(datasets.Value("float32")),
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}
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# "purity": {
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# "scene": datasets.Sequence(datasets.Value("float32")),
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# "action": datasets.Sequence(datasets.Value("float32")),
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# "rationale": datasets.Sequence(datasets.Value("float32")),
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# },
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# "diversity": {
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# "scene": datasets.Value("float32"),
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# "action": datasets.Value("float32"),
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# "rationale": datasets.Value("float32"),
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# },
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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image_files = dl_manager.download(_IMG)
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annotation_files = dl_manager.download_and_extract([_TRAIN, _TEST])
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"annotation_file_path": annotation_files[0],
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"images": dl_manager.iter_archive(image_files),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"annotation_file_path": annotation_files[1],
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"images": dl_manager.iter_archive(image_files),
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},
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),
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]
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def _generate_examples(self, annotation_file_path, images):
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idx = 0
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#assert Path(annotation_file_path).suffix == ".jsonl"
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with open(annotation_file_path, "r") as fp:
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metadata = {json.loads(item)['file_name']: json.loads(item) for item in fp}
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# This loop relies on the ordering of the files in the archive:
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# Annotation files come first, then the images.
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for img_file_path, img_obj in images:
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file_name = Path(img_file_path).name
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if file_name in metadata:
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yield idx, {
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"file_name": file_name,
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"image": {"path": img_file_path, "bytes": img_obj.read()},
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"scene": metadata[file_name]['captions']['scene'],
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"action": metadata[file_name]['captions']['action'],
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"rationale": metadata[file_name]['captions']['rationale'],
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"object": metadata[file_name]['captions']['object'],
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"confidence": metadata[file_name]['confidence'],
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}
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idx += 1
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