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Home > All Category Datasets > LLM Datasets > 1,400 Human Action Image Dataset with 5,937 Boxes Annotate Data

1,400 Human Action Image Dataset with 5,937 Boxes Annotate Data

human action dataset
human activity image dataset
action recognition images
annotated human activity dataset
human image captioning dataset
multi-modal human dataset
human action detection data
VLA dataset

1,400 Human Action Image Dataset with 5,937 Boxes Annotate Data collected a variety of scenes and human activities. Each person in the image is annotated with detailed descriptions.This data can provide a rich resource for large multi-modal models. It has been validated by multiple AI companies and proves beneficial for achieving outstanding performance in real-world applications. Throughout the process of Dataset collection, storage, and usage, we have consistently adhered to dataset protection and privacy regulations to ensure the preservation of user privacy and legal rights. All Dataset comply with regulations such as GDPR, CCPA, PIPL, and other applicable laws.

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SpecificationsSpecifications
Data size
1,400 images, each image has a json file and a metadata file
Collection environment
cafes, convenience stores
Race distribution
Koreans
Collection diversity
multiple scenes, multiple human actions
Data formats
the image format is .jpg
Language
English
JSON annotation content
person ID, gender, age, behavior, behavior description, whether blocked, person rectangle
Metadata annotation content
shooting date, location, camera height, position matching degree
Image resolution
resolution ≥ 1080p
Annotation
bounding boxes closely fitting the person edges are correct. Both bounding box accuracy and label accuracy should be no less than 97%
Sample Sample
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What can Nexdata’s LLM datasets be used for?

Nexdata’s LLM datasets can support a wide range of large language model development tasks, including pre-training, supervised fine-tuning, instruction tuning, preference optimization, evaluation, and domain-specific model development. Depending on the dataset, data may include text, instruction-response pairs, conversations, question-answer pairs, reasoning data, and other structured or annotated content.

Can Nexdata customize LLM datasets based on our specific model and requirements?

Yes. If our off-the-shelf LLM datasets do not fully match your requirements, Nexdata provides flexible custom data collection, generation, annotation, curation, and quality control services. We can customize datasets based on your target languages, domains, use cases, data formats, task types, volume, and quality requirements to support specific LLM training and evaluation projects.

Can Nexdata provide large-scale and high-quality data for LLM development?

Yes. Nexdata can support large-scale LLM data projects across multiple languages, domains, and data types. Our data services include multi-stage quality control, data cleaning, annotation, validation, and curation to help ensure consistency and usability. For projects requiring data beyond our existing datasets, our customized data services can be scaled according to the required volume, specifications, and delivery schedule.

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