Standard DatasetsPupils Segmentation Dataset
The progress of video and photo editing applications relies heavily on high-quality datasets for machine learning models training. Our carefully selected datasets play a crucial role in enhancing the abilities of such applications, by offering accurate segmentation and recognition of different elements within images and videos.
The "Pupils Segmentation Dataset" is tailored for applications in the beauty and media & entertainment industries, consisting of internet-collected images with resolutions varying from 90 x 89 to 419 x 419 pixels. This dataset focuses on semantic segmentation, providing subdivision annotations specifically for pupil locations to enhance detailed eye-related features in digital content.
Sample
Specification
Dataset ID
MD-Image-029
Dataset Name
Pupils Segmentation Dataset
Data Type
ImageVolume
About 17k
Data Collection
Internet collected images. Resolution ranges from 90 x 89 to 419 x 419 pixels.
Annotation
Semantic Segmentation
Annotation Notes
Subdivision annotation of pupil locations.
Application Scenarios
Media & Entertainment;Beauty
Data Collections
This dataset includes approximately 17k images, each offering precise annotations for the segmentation of pupil locations. The specialized focus on pupils makes it an invaluable tool for developing advanced beauty apps, virtual makeovers, and enhancing the realism of characters in visual entertainment content, by providing accurate data for eye feature analysis and augmentation.
Quality Assurance
Relevant Open Datasets
To supplement our Face Parsing Dataset, users can explore these open datasets for additional resources:
FASSEG Repository [Learn more]
This collection offers datasets for frontal face segmentation (Frontal01 and Frontal02) and a dataset for faces in multiple poses (Multipose01).These datasets can be valuable for training models to perform face segmentation in different orientations and conditions.
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