In machine learning, bbox (bounding box) detection acts like a digital treasure hunt within images. We train a model to unearth objects and mark their location with a rectangular box. Unlike image classification that just sorts images into categories, bbox detection pinpoints exactly where the object is. The model learns from a treasure map of sorts – a dataset with images where objects are surrounded by bounding boxes. Deep learning models like YOLO, SSD (Single Shot MultiBox Detector), and Faster R-CNN excel at this task, efficiently sifting through image data to find objects and mark their territory. After training, the model becomes an expert treasure hunter, uncovering objects and their locations in new images. This skill is crucial for tasks like autonomous vehicles that need to identify and react to objects around them, or medical imaging analysis where pinpointing specific regions is vital.
- We handle both image and video formats for bbox detection. In images, we aim to identify and localize objects within each frame by drawing bounding boxes around them and labeling their content. For videos, bounding boxes with labels are predicted for every frame, effectively tracking and labeling the objects throughout the video.
- Streamlining the process, we eliminate the need for a specific folder structure on your end. Our internal systems efficiently manage all organizational aspects.
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Transparent Pricing Structure
We follow a clear pricing structure for our BBox detection annotation services. Here’s a breakdown of the key pricing structure:
- Fixed Fee for Small Batches: Up to 10,000 annotations cost a flat fee of $100 per batch, regardless of the number of images within that batch.
- Per-Annotation Pricing for Larger Batches: For batches beyond 10000 annotations, you pay $0.01 per annotation.
To initiate work, you prepay a portion of the total cost based on the batch size, tiered upfront payments are as follow:
- $100 for batches between 10,000 and 50,000 annotations.
- $500 for batches between 50,000 and 200,000 annotations.
- $2,000 for batches between 200,000 and 400,000 annotations.
- 25% upfront payment for batches exceeding 400,000 annotations.
After the annotations are complete, you pay the remaining balance based on the per-annotation cost.
Understanding Project Complexity
We understand that for some projects, especially those involving complex or subjective BBox detection tasks, accurately estimating the number of annotations upfront can be challenging. We offer flexibility in such cases:.
- Estimated Annotation Range: If you're unsure of the exact number of annotations needed, you can provide an estimated range. We'll quote based on that range with a buffer to account for potential variations.
- Pilot Batch Option: For highly complex projects, consider a pilot batch of a few thousand images. This allows us to assess the annotation difficulty and provide a more accurate quote for the entire project.
- Flexible Payment Adjustments: During the annotation process, if the actual number of annotations deviates significantly from the initial estimate, we can adjust the final cost accordingly.
Transparency and Communication
To ensure a smooth and collaborative process we aim for clear communication, centralized information management, and the flexibility to adapt to the specific needs of your project:
- Ticketing System: We recommend creating a ticket in our system to centralize all communication regarding your project. Through the ticket system, we can easily track progress reports, answer your specific questions and requirements, and discuss any adjustments needed throughout the annotation process.
- Open Communication: We believe in open communication. We'll keep you informed about the annotation progress through the ticketing system and proactively reach out if any potential adjustments to the initial estimate are necessary due to project complexity.