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Polygon Annotation
Precise multi-point polygon annotation for Deep Learning
![spatial data analytics](https://sp-ao.shortpixel.ai/client/q_lossy,ret_img,w_604,h_340/https://sp-ao.shortpixel.ai/client/q_lossy,ret_img,w_1024/https://taqadam.io/wp-content/uploads/2019/11/solar-florida-1024x576.jpg)
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Polygons and Area annotation: Deep Learning
How it Works
Polygons are used in the models where the objects do not have a regular shape, and require precision.
Challenges and solutions:
* Pixel-level accuracy. Our custom designed image annotation tools allow drawing precisely the borders of the object and record the maximim x/y points for the Deep Learning model. COCO format allows machine learning engineers to use the appropriate shape in class training, interchangeably between using the output recorded as rectangle or multi-point polygon.
* Geospatial. If the the polygonal annotation is a part of physical footprint mapping, where the borders of the objects (container ships, cranes) matter, choosing polygon annotation as a tool is important. In addition, to free line polygon, at TaQadam we used ellipses and other standard shapes to increase the speed.
Polygon annotation drawing
Why TaQadam: We Make Visual Data AI-Ready
Image Annotation company with a complete solution on AI data training:
Image annotation tool, Data Management Platform and Trained Teams
- Quality Assured Annotation
- Managed Teams
- Standard or Custom Data Output
- Industry Specific Expertise
- Data Management Platform
- No Project Management Fee
- Security and Non-Disclosure