In the dynamic world of machine learning and computer vision, high-quality annotations are the foundation of successful models. However, the annotation process can be time-consuming and resource-intensive. Let's explore tips to significantly boost your annotation speed, without compromising accuracy, inside the Kognic platform.
Why efficient annotations matter
Before diving into specific tips, let's consider why efficient annotations are crucial. In the AI development pipeline, annotations often become a bottleneck, potentially slowing down model training and iteration. By streamlining this process, we can accelerate development cycles, reduce costs, and bring solutions to market faster - all key factors in staying ahead of your competitors.
4 Ways Kognic Maximizes Your Annotated Data Output
- Leverage Auto-Labels with Co-Pilot Kognic's Co-Pilot uses your model's predictions (or our foundation models) as a starting point for annotation. Instead of drawing objects from scratch, annotators review and refine existing labels—reducing annotation time by up to 68%. Even imperfect auto-labels deliver substantial cost savings, as human effort shifts from creation to validation. This is one of the cornerstone of our productivity advantage.
- Streamline Workflows with Machine-Assisted Tools Kognic automates repetitive tasks that computers handle well, so annotators focus on judgment calls that require human expertise. For example, our machine-assisted cuboid tool lets annotators place just two points—front and back of an object—and the platform automatically generates a properly sized 3D bounding box. These intelligent tools compound productivity gains across large datasets.
- Implement Guided Workflows Kognic's guided workflows organize annotation tasks in the most efficient sequence, leveraging automation at each step. This structured approach ensures consistency across teams, minimizes errors, and maximizes throughput. By guiding annotators through optimized task sequences, you handle larger datasets more effectively and accelerate model development cycles.
- Optimize with Keyboard Shortcuts Proficiency with customized keyboard shortcuts dramatically reduces time on repetitive actions. Kognic allows full customization of shortcuts to match individual annotator preferences—an investment that pays dividends in long-term efficiency. For instance, assign 'T' to your tape measure and 'Shift+S' to scissors, then watch productivity compound across thousands of annotations.
Maintaining Quality at Speed
Productivity means nothing without accuracy. That's why Kognic includes robust quality assurance built into the platform.
Kognic's Continuous Quality Control (CQC) is a useful tool for keeping annotations accurate. It works by checking a sample of the annotations to estimate the overall quality. CQC also allows managers to break large annotation tasks into smaller batches, where each batch goes through its own quality check.
By implementing these tips, you can create a more efficient annotation pipeline that not only speeds up the process but also maintains the high-quality standards required for developing accurate and reliable AI models. Remember, the goal is not just to annotate faster, but to optimize the entire annotation workflow for both speed and precision - because with annotations, every second counts.