Swimsuit Human Segmentation Dataset with 14,358 Photos and Body-Part Masks

UniDataPro's Swimsuit Human Segmentation Dataset comprises 14,358 high-quality photos of 7,179 people wearing bathing suits, each paired with detailed segmentation masks. It is designed for semantic and instance segmentation tasks, offering manually annotated labels for training deep learning models in human body analysis. The dataset was last updated on 2025-08-29.

Use Cases

• Train semantic segmentation models based on the detailed body-part masks mentioned in the description.
• Develop instance segmentation models to distinguish between multiple people in images based on the dataset's instance-level annotations.
• Benchmark model performance on human parsing tasks in swimwear contexts using the high-quality photos and manual labels.
• Fine-tune models for applications in fashion or fitness analysis based on the dataset's focus on bathing suits and body segmentation.

Strengths

• Contains 14,358 high-quality photos, providing a substantial volume of training data.
• Includes 7,179 unique people of diverse genders, suggesting representation across demographics.
• Features manually annotated segmentation masks, which likely indicates high label accuracy.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

UniDataPro on Hugging Face

Collection Method

Likely collected and manually annotated for computer vision tasks.

Freshness

Last updated 2025-08-29 16:55:58; freshness should be verified.