Use predictions to prelabel tasks in segmentation tasks #7546
Description
Is your feature request related to a problem? Please describe.
Yes. In segmentation tasks, when using model predictions to prelabel data, inaccurate boundary predictions require manual fine-tuning. However, densely packed data points (e.g., in high-resolution or complex-scene datasets) make precise boundary adjustments extremely time-consuming and inefficient, as manual editing struggles to navigate or refine dense point distributions effectively.
Describe the solution you'd like
I haven’t found a convenient option in Label Studio to adjust dense data points. I’m wondering if there are related tools or workflows that can help with this.
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
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