datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
clevr-multichange
CLEVR-Multi-Change (30–40 objects)
Two-image change-captioning data used in "Stateful Visual Encoders for
Vision-Language Models" (the Multi-object Visual Differencing task). Each example is a before/after pair of a CLEVR scene
with 30–40 objects and 4 simultaneous changes (add / delete / move /
replace), rendered at 768×768 with a wide camera angle. Built with the
CLEVR-Multi-Change engine (Johnson et al. 2017; Qiu et al. 2021).
Code & paper:… See the full description on the dataset page: https://huggingface.co/datasets/zwcolin/clevr-multichange.CLEVR-BT-DB
How to install?
!pip install datasets -q
from huggingface_hub import snapshot_download
import pandas as pd
import matplotlib.pyplot as plt
# First step: download an entire datatset
snapshot_download(repo_id="Aborevsky01/CLEVR-BT-DB", repo_type="dataset", local_dir='path-to-your-local-dir')
# Second step: unarchive the images for VQA
!unzip [path-to-your-local-dir]/[type-of-task]/images.zip
# Example of the triplet (image - question -… See the full description on the dataset page: https://huggingface.co/datasets/Aborevsky01/CLEVR-BT-DB.clevr_r1
CLEVR R1
CLEVR R1 is a multimodal reasoning dataset generated with R1 to distill multimodal reasoning abilities into models. This dataset was taken from MMInstruction/Clevr_CoGenT_TrainA_R1.
clevr-tr
Dataset Card for CoT
Dataset Sources
Repository: LLaVA-CoT GitHub Repository
Paper: LLaVA-CoT on arXiv
Dataset Structure
Turkish - tr dataset
unzip image.zip
The train.jsonl file contains the question-answering data and is structured in the following format:
{
"id": "example_id",
"image": "example_image_path",
"conversations": [
{"from": "human", "value": "Lütfen resimdeki kırmızı metal nesnelerin sayısını belirtin."},
{"from": "gpt", "value":… See the full description on the dataset page: https://huggingface.co/datasets/berhaan/clevr-tr.CLEVR-MATE
CLEVR-MATE
MATE-like cross-modal entity linking dataset generated from CLEVR-style scenes for probe training.
Variants
Config
Renderer
Scenes
Samples
Strict
Description
2d
Pillow
3,000
18,000
No
Fast 2D shape rendering
pyrender
pyrender
3,000
18,000
No
Offscreen 3D rendering
blender
Blender Cycles
3,000
18,000
No
Photorealistic ray-traced rendering
2d_strict
Pillow
3,000
18,000
Yes
2D, strict cross-modal
pyrender_strict
pyrender
3,000
18,000
Yes
3D… See the full description on the dataset page: https://huggingface.co/datasets/qinglinhou/CLEVR-MATE.