A telecommunications software company in Finland required image annotation services to label people in images with bounding boxes. They sought a reliable solution for maintaining high-quality annotations despite having a low monthly annotation load.
The primary challenge faced in this project was ensuring coherent annotations while multiple annotators worked in parallel on the same dataset. Maintaining consistent identification (IDs) within the project was crucial to avoid discrepancies in the annotations.
Our Data Annotation Approach:
In response to the unique challenges of our project, we implemented a comprehensive range of solutions that emphasized efficiency, expertise, and exceptional quality throughout every phase:
We initiated the project by configuring the Computer Vision Annotation Tool (CVAT), providing an efficient platform for image annotation.
We carefully vetted annotators with proven experience in bounding box annotation to ensure expertise.
Test Task Excellence:
We completed a test task involving 100 images within 48 hours, receiving positive feedback from the client. This effort led to our shortlisting as one of the top three vendors based on the quality-to-price ratio.
Dedicated Part-Time Annotator:
Given the low monthly annotation load, we assigned one dedicated part-time annotator to ensure consistency in annotation quality.
Quality Assurance (QA) Specialist:
To maintain the highest quality of annotation despite the small team, we added a QA specialist to the project. Their role was to review and verify annotations for accuracy.
We commenced an ongoing project for the monthly labeling of 2-3k video frames, completing each batch within an impressive 36-hour timeframe upon receiving the files.
Our commitment to excellence and efficiency in image annotation, combined with our dedication to meeting project challenges, yielded remarkable results. Despite a relatively modest monthly annotation load, we achieved:
Learn More About Our Expertise
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