Accurate bounding box labeling is most important for the best performance of an object detection model. At FcosAI, our dedicated highly trained annotator performs annotation for various tasks starting from bounding box labeling for e-commerce product type detection, pedestrians detection, blood cell detection, car's number plate detection and many more. We provide the annotation output as the customer specified any format. This annotation box could be used for object detection, object classification, weekly supervision for semantic segmentation to empower your AI model. Following are few use cases we've handled -
1. E-Commerce Product Types Detection
This type of bounding boxes could be used for e-commerce product type detection which is the main component for product search engines based on visual/image similarity, product matching, and recommendation system. We provide detailed labeling starting from small fashion accessories to large objects like furniture and all.
2. Pedestrians Detection
Pedestrian detection dataset can be used for various security anomaly identification problem in traffic signal, road, footpath. Our bounding box labeling for pedestrians detection can enrich your model for this purpose.
3. Blood Cell Detection
This type of annotation could be used for a medical diagnosis for different blood cell detection. The diagnosis of blood-based diseases often involves identifying and characterizing patient blood samples. Automated methods to detect and classify blood cell subtypes have important medical applications.
4. Vehicle Number Plate Detection
Vehicle Number Plate Detection aims at the detection of the License Plate present on a vehicle and then extracting the contents of that License Plate. A vehicle’s license plate is commonly known as ‘a number plate’. It is a metal plate that is attached to a vehicle and has the official registration number of a vehicle embossed on it. We provide bounding box and text extraction annotation for vehicle registration plat detection.
If you are looking to scale up your image labeling needs to empower your model, try FcosAI.