instruction
string
| inputs
string
| image_base64_str
list
| outputs
string
|
---|---|---|---|
"Scrutinize the given image and answer the connected question, using your commonsense and world knowledge. Provide a brief explanation that highlights the key factors and reasoning behind your answer." | "What is the man by the bags awaiting?" | [
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"
] | "Based on the given rationales and the image, it is clear that the man in the image is waiting for a cab. The option of a train can be ruled out since trains don't typically operate on the street. Similarly, the option of delivery doesn't make sense as the man is already by the bags, implying that he is the one traveling with them rather than awaiting a delivery. The presence of a skateboarder not paying attention to the man also suggests that the skateboarder is not relevant to the man's purpose. Hence, the correct answer is cab." |
"For the presented image, provide a well-reasoned answer to the corresponding question, using your u(...TRUNCATED) | "Where does this man eat pizza?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "Based on my analysis of the image, the man can be seen eating pizza at a work desk, which strongly (...TRUNCATED) |
"Analyze the given image and respond to the associated question with a correct answer. Justify your (...TRUNCATED) | "What is the occupation of the person driving?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "The person driving in the image appears to be a farmer. This conclusion is supported by the presenc(...TRUNCATED) |
"For the presented image, provide a well-reasoned answer to the corresponding question, using your u(...TRUNCATED) | "How were the drivers of the cars able to park here?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "The cars in the image are parked on a tarmac near an airplane, indicating that they are in an area (...TRUNCATED) |
"Investigate the image and determine an accurate response to the corresponding question. Deliver a s(...TRUNCATED) | "How many people can ride this motorcycle at a time?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "By looking at the image, it can be observed that there is a passenger seat and a driver's seat on t(...TRUNCATED) |
"Analyze the given image and respond to the associated question with a correct answer. Justify your (...TRUNCATED) | "Where would one most likely see the show advertised in the poster?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "Based on the image and the information provided in the rationales, one would most likely see the sh(...TRUNCATED) |
"For the presented image, provide a well-reasoned answer to the corresponding question, using your u(...TRUNCATED) | "What mood do the cows seem to be in?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "The cows in the image seem to be in a happy mood. They have their heads up and appear satisfied as (...TRUNCATED) |
"For the presented image, provide a well-reasoned answer to the corresponding question, using your u(...TRUNCATED) | "What type of rain is this called?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "Judging from the way the woman is using her umbrella to shield herself from the rain, it appears th(...TRUNCATED) |
"Based on the image, generate a fitting answer for the linked question. In addition, give a brief ra(...TRUNCATED) | "What is the man putting on the bus?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "Based on the evidence in the image, it appears that the man is putting a big red bow on the bus. We(...TRUNCATED) |
"Observe the image and address the connected question, supplying an accurate answer along with a con(...TRUNCATED) | "If the cameraman were driving what do they have to do from this position?" | ["/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLD(...TRUNCATED) | "If the cameraman were driving from this position, they would have to turn right. This is suggested (...TRUNCATED) |
Dataset Card for M3IT
Project Page: M3IT
Languages
English and Chinese. 80 translated version can be found at M3IT-80.
Dataset Statistics
Our dataset compiles diverse tasks of classical vision-language tasks, including captioning, visual question answering~(VQA), visual conditioned generation, reasoning and classification.
Instruction Statistics
Task | #Instructions |
---|---|
Image Captioning | 52 |
Classification | 113 |
Visual Question Answering | 95 |
Knowledgeable Visual QA | 40 |
Reasoning | 60 |
Generation | 40 |
Total | 400 |
Task Statistics
Task | Description | #Train | #Val | #Test |
---|---|---|---|---|
Image Captioning | Given an image, write a description for the image. | 679,087 | 41,462 | 27,499 |
Classification | Given an image, classify the image into pre-defined categories. | 238,303 | 100,069 | 21,206 |
Visual Question Answering | Given an image, answer a question relevant to the image. | 177,633 | 46,314 | 10,828 |
Knowledgeable Visual QA | Given an image, answer the question requires outside knowledge. | 39,981 | 11,682 | 5,477 |
Reasoning | Given an image, conduct reasoning over the images. | 99,372 | 11,500 | 10,000 |
Generation | Given an image, make compositions with certain requirements. | 145,000 | 11,315 | 17,350 |
Chinese | CAP, CLS, VQA, and GEN tasks in Chinese. | 192,076 | 77,306 | 4,100 |
Video | CAP, CLS, and VQA tasks on video-language datasets. | 20,868 | 7,542 | 9,294 |
Multi-lingual | Translated tasks in 80 languages | 0 | 240,000 | 184,000 |
Detailed Dataset Statistics
Task | Dataset | #Train | #Val | #Test |
---|---|---|---|---|
Image Captioning | coco |
566,747 | 25,010 | 25,010 |
textcap |
97,765 | 13,965 | 0 | |
image-paragraph-captioning |
14,575 | 2,487 | 2,489 | |
Classification | coco-goi |
30,000 | 2,000 | 0 |
coco-text |
118,312 | 27,550 | 0 | |
imagenet |
30,000 | 50,000 | 0 | |
coco-itm |
30,000 | 5,000 | 5,000 | |
snli-ve |
20,000 | 14,339 | 14,740 | |
mocheg |
4,991 | 180 | 466 | |
iqa |
5,000 | 1,000 | 1,000 | |
Visual Question Answering | vqa-v2 |
30,000 | 30,000 | 0 |
shapes |
13,568 | 1,024 | 1,024 | |
docvqa |
39,463 | 5,349 | 0 | |
ocr-vqa |
11,414 | 4,940 | 0 | |
st-vqa |
26,074 | 0 | 4,070 | |
text-vqa |
27,113 | 0 | 5,734 | |
gqa |
30,001 | 5,001 | 0 | |
Knowledgeable Visual QA | okvqa |
9,009 | 5,046 | 0 |
a-okvqa |
17,056 | 1,145 | 0 | |
science-qa |
12,726 | 4,241 | 4,241 | |
viquae |
1,190 | 1,250 | 1,236 | |
Reasoning | clevr |
30,000 | 2,000 | 0 |
nlvr |
29,372 | 2,000 | 0 | |
vcr |
25,000 | 5,000 | 5,000 | |
visual-mrc |
15,000 | 2,500 | 5,000 | |
winoground |
0 | 0 | 800 | |
Generation | vist |
5,000 | 4,315 | 4,350 |
visual-dialog |
50,000 | 1,000 | 1,000 | |
multi30k |
90,000 | 6,000 | 12,000 | |
Chinese | fm-iqa |
164,735 | 75,206 | 0 |
coco-cn |
18,341 | 1,000 | 1,000 | |
flickr8k-cn |
6,000 | 1,000 | 1,000 | |
chinese-food |
0 | 0 | 1,100 | |
mmchat |
3,000 | 1,000 | 1,000 | |
Video | ss |
2,000 | 2,000 | 2,000 |
ivqa |
5,994 | 2,000 | 2,000 | |
msvd-qa |
1,161 | 245 | 504 | |
activitynet-qa |
3,200 | 1,800 | 800 | |
msrvtt |
6,513 | 497 | 2,990 | |
msrvtt-qa |
2,000 | 1,000 | 1,000 |
Dataset Structure
HuggingFace Login (Optional)
# OR run huggingface-cli login
from huggingface_hub import login
hf_token = "hf_xxx" # TODO: set a valid HuggingFace access token for loading datasets/models
login(token=hf_token)
Data Loading
from datasets import load_dataset
ds_name = "coco" # change the dataset name here
dataset = load_dataset("MMInstruction/M3IT", ds_name)
Data Splits
from datasets import load_dataset
ds_name = "coco" # change the dataset name here
dataset = load_dataset("MMInstruction/M3IT", ds_name)
train_set = dataset["train"]
validation_set = dataset["validation"]
test_set = dataset["test"]
Data Instances
from datasets import load_dataset
from io import BytesIO
from base64 import b64decode
from PIL import Image
ds_name = "coco" # change the dataset name here
dataset = load_dataset("MMInstruction/M3IT", ds_name)
train_set = dataset["train"]
for train_instance in train_set:
instruction = train_instance["instruction"] # str
inputs = train_instance["inputs"] # str
outputs = train_instance["outputs"] # str
image_base64_str_list = train_instance["image_base64_str"] # str (base64)
image_0 = Image.open(BytesIO(b64decode(image_base64_str_list[0])))
Data Fields
import datasets
features = datasets.Features(
{
"instruction": datasets.Value("string"),
"inputs": datasets.Value("string"),
"image_base64_str": [datasets.Value("string")],
"outputs": datasets.Value("string"),
}
)
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Task | Dataset [Citation] | Source |
---|---|---|
Image Captioning | coco [1] |
Source |
textcap [2] |
Source | |
image-paragraph-captioning [3] |
Source | |
Classification | coco-goi [1] |
Source |
coco-text [4] |
Source | |
imagenet [5] |
Source | |
coco-itm [1] |
Source | |
snli-ve [6] |
Source | |
mocheg [7] |
Source | |
iqa [8] |
Source | |
Visual Question Answering | vqa-v2 [9] |
Source |
shapes [10] |
Source | |
docvqa [11] |
Source | |
ocr-vqa [12] |
Source | |
st-vqa [13] |
Source | |
text-vqa [14] |
Source | |
gqa [15] |
Source | |
Knowledgeable Visual QA | okvqa [16] |
Source |
a-okvqa [17] |
Source | |
science-qa [18] |
Source | |
viquae [19] |
Source | |
Reasoning | clevr [20] |
Source |
nlvr [21] |
Source | |
vcr [22] |
Source | |
visual-mrc [23] |
Source | |
winoground [24] |
Source | |
Generation | vist [25] |
Source |
visual-dialog [26] |
Source | |
multi30k [27] |
Source | |
Chinese | fm-iqa [28] |
Source |
coco-cn [29] |
Source | |
flickr8k-cn [30] |
Source | |
chinese-food [31] |
Source | |
mmchat [32] |
Source | |
Video | ss [33] |
Source |
ivqa [34] |
Source | |
msvd-qa [35] |
Source | |
activitynet-qa [36] |
Source | |
msrvtt [35] |
Source | |
msrvtt-qa [37] |
Source |
Annotations
Annotation process
To build high-quality multimodal instruction datasets, we rewrite various datasets into multimodal-to-text dialog format. The annotation process includes four steps:
- (1) Stage I: Instruction Writing: writing instructions for each task;
- (2) Stage II: Data Format Unification: structuring images and texts into a unified schema;
- (3) Stage III: Quality Check: checking the overall dataset quality;
- (4) Stage IV: Key Datasets Translation: building multilingual sets.
Who are the annotators?
Eight authors of this work are employed as human annotators, each of whom is a graduate student familiar with relevant literature.
Additional Information
Licensing Information
The content of original dataset follows their original license. We suggest that for the task with Unknown/Custom license, the user can check the original project or contact the dataset owner for detailed license information.
Our annotated instruction data is licensed under CC BY 4.0.
Citation Information
@article{li2023m3it,
title={M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning},
author={Lei Li and Yuwei Yin and Shicheng Li and Liang Chen and Peiyi Wang and Shuhuai Ren and Mukai Li and Yazheng Yang and Jingjing Xu and Xu Sun and Lingpeng Kong and Qi Liu},
journal={arXiv preprint arXiv:2306.04387},
year={2023}
}
Contributions
M3IT is an open-source, large-scale Multi-modal, Multilingual Instruction Tuning dataset, designed to enable the development of general-purpose multi-modal agents.
References
- [1] Microsoft COCO: Common Objects in Context
- [2] TextCaps: a dataset for image captioning with reading comprehension
- [3] A Hierarchical Approach for Generating Descriptive Image Paragraphs
- [4] COCO-Text: Dataset and benchmark for text detection and recognition in natural images
- [5] Imagenet large scale visual recognition challenge
- [6] E-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks
- [7] End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models
- [8] Quantifying visual image quality: A Bayesian view
- [9] Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering
- [10] Neural Module Networks
- [11] DocVQA: A dataset for vqa on document images
- [12] OCR-VQA: Visual Question Answering by Reading Text in Images
- [13] Scene Text Visual Question Answering
- [14] Towards VQA Models That Can Read
- [15] GQA: A new dataset for real-world visual reasoning and compositional question answering
- [16] OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge
- [17] A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge
- [18] Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
- [19] ViQuAE: a dataset for knowledge-based visual question answering about named entities
- [20] CLEVR: A diagnostic dataset for compositional language and elementary visual reasoning
- [21] A Corpus of Natural Language for Visual Reasoning
- [22] From recognition to cognition: Visual Commonsense Reasoning
- [23] VisualMRC: Machine reading comprehension on document images
- [24] WinoGround: Probing vision and language models for visio-linguistic compositionality
- [25] Visual Storytelling
- [26] Visual Dialog
- [27] Multi30k: Multilingual english-german image descriptions
- [28] Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question
- [29] COCO-CN for cross-lingual image tagging, captioning, and retrieval
- [30] Adding Chinese Captions to Images
- [31] ChineseFoodNet: A large-scale image dataset for chinese food recognition
- [32] MMChat: Multi-Modal Chat Dataset on Social Media
- [33] The "Something Something" Video Database for Learning and Evaluating Visual Common Sense
- [34] Just Ask: Learning to answer questions from millions of narrated videos
- [35] Video Question Answering via Gradually Refined Attention over Appearance and Motion
- [36] ActivityNet-qa: A dataset for understanding complex web videos via question answering
- [37] MSR-VTT: A large video description dataset for bridging video and language
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