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Human Daily Life Activities Dataset (4,000 Images)
Generative AI & Computer Vision
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£199
About
This dataset contains 4,000 high-quality JPG images capturing daily life activities performed by children, adults, families, and elderly individuals. Scenes include real interactions in natural settings, both indoors (homes, kitchens, bedrooms, living areas) and outdoors (streets, parks, nature areas). Activities range from housework and learning to hobbies, family moments, exercise, and everyday routines, making the dataset suitable for a wide variety of AI and computer vision applications.
Dataset Features
List and describe each column or key feature of the dataset.
- Subjects: Children, adults, seniors; individual and group interactions.
- Activities Covered: Housework, cooking, eating/drinking, studying, music practice, hobbies (e.g., knitting), playing, walking outdoors, family interactions, self-care actions.
- Locations: Indoor home environments, private gardens, streets, parks, natural areas.
- Image Type: High-resolution JPG photographs captured with professional equipment.
- Variability: Wide range of ages, poses, lighting conditions, environments, and actions.
- Uniqueness: All images are original and carefully curated.
Distribution
Detail the format, size, and structure of the dataset.
- Data Volume: 4,000 individual JPG images.
- Organization: Provided as a single ZIP archive with structured naming.
- Resolution: Majority between 3000–6000 px on the longest side.
- Structure: One unified folder for easy ingestion into ML pipelines.
Usage
This dataset is ideal for a variety of applications:
- Application: Human action recognition and multi-class activity classification.
- Application: Computer vision models for daily household activity understanding.
- Application: Generative AI training for realistic human scenes and behaviors.
- Application: Robotics & assistive robotics (context recognition, manipulation tasks).
- Application: Family and child-related AI systems (education, safety, wellness).
- Application: Smart home and IoT behavior modeling.
- Application: Elderly-care AI applications (movement, mobility, exercise routines).
- Application: Multimodal training datasets for vision-language models.
Coverage
Explain the scope and coverage of the dataset:
- Geographic Coverage: Italy; suitable for global model training.
- Time Range: Images captured between 2024 and 2025.
- Demographics: Children (6+), adults, elderly individuals; mixed gender and roles.
License
Proprietary
Who Can Use It
List examples of intended users and their use cases:
- Data Scientists: For action recognition models, segmentation, classification.
- Researchers: For human behavior analysis, robotics, and multimodal studies.
- Businesses: For smart home AI, family-focused solutions, generative AI R&D.
- AI Companies: For refining human realism and contextual understanding in models.
- Developers: For computer vision pipelines, pose-estimation, scene understanding.
Include any additional notes or context about the dataset that might be helpful for users.
- All photos are original and fully owned by Alessandro Grandini.
- All individuals provided full authorization for dataset distribution and AI usage.
- No images were generated by AI.
- Photos include children, adults, and seniors performing genuine real-life actions.
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