Keylabs, a prominent name in data annotation, has recently enhanced its platform with the integration of the ‘Spot Healing Tool’ and ‘Edge Smoothing Tool’, focusing on improving the speed and efficiency of data annotation in the realm of AI and machine learning.

The ‘Spot Healing Tool’ addresses common anomalies in AI-assisted annotation, such as the occurrence of small holes and isolated pixel groups, known as ‘islands’, in the annotated areas. This feature is adept at automatically detecting and removing these artifacts, which not only cleans up the data but also significantly accelerates the annotation process.

Similarly, the ‘Edge Smoothing Tool’ is developed to refine the edges of annotated objects within images or videos. Often, manual annotation results in jagged edges that can be time-consuming to correct. This tool utilizes advanced algorithms for automatically adjusting these edges, making them more precise and closer to the object’s actual shape. This not only improves the quality of the annotations but also quickens the overall process.

In a statement, Michael Abramov, CEO at Keylabs, highlighted the impact of these new features, “The introduction of the Spot Healing and Edge Smoothing tools marks a significant leap in the efficiency of data annotation. By streamlining these aspects of the annotation process, we are enabling professionals in AI and machine learning to accelerate their workflow and focus on more complex tasks.”

These new tools are in line with Keylabs’ commitment to offering solutions that enhance productivity and efficiency in data annotation. Now available on the Keylabs data labeling platform, the Spot Healing and Edge Smoothing tools are set to transform the speed and efficiency with which data is prepared for AI development.

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