Clothes segmentation is the process of identifying and separating individual clothing items in images or videos.Our company provides a one-stop solution to this challenge, offering manually annotated images with precisely defined regions of clothing items according to your specifications.
Our service excels in terms of diversity, quality annotations, large size, and representativeness. The range of clothing items, various ethnicities, ages, genders, lighting conditions, and poses are carefully selected to meet your needs.
Our annotations are meticulous and consistent, ensuring the models trained on our data perform at their best. Additionally, our datasets are substantial, resulting in stronger models. We also make sure that our datasets reflect the real-world distribution of faces that the model will encounter.
We use two techniques for clothes segmentation, including Bounding Boxes and Polygonal Segmentation:
- Bounding Boxes involve drawing a rectangular box around each clothing item in an image, outlining its boundaries.
- Polygonal Segmentation involves manually tracing the boundaries of each clothing item using a set of connected line segments, creating a polygonal mask.
Our experienced team is equipped to efficiently gather and annotate the required dataset for your specific project, ensuring that you receive the best results.