Select a Model

DaoAI World supports the following models:

• Supervised Defect Segmentation

• Unsupervised Defect Segmentation

• Positioning

• Presence Detection

• Instance Segmentation

• Keypoint Detection

• Image Classification

• Object Detection

• OCR

How to Choose a Model? Different models have their own unique features and best-use cases. Here are some points to help you select the right model:

• Detecting objects in an image:

  • Object Detection : Detects the type and bounding box of an object. Use this model when you need to detect the presence of objects in an image. Example scenarios: detecting the number of vehicles on the road, checking if screws are installed or missing in a part, detecting whether workers are wearing helmets.

    

  • Instance Segmentation : Detects the type and mask of an object. Use this model when you need to detect the presence of objects and their masks. Example scenarios: identifying the position and area of a package, locating parts inside a box, or classifying different types of screws in one image.

    

  • Keypoint Detection : Detects the type , mask , and keypoints/pose of an object. Use this model when you need instance segmentation with additional keypoint detection. Example scenarios: detecting the posture of athletes, determining the current position and rotation of an object.

    

• Image Classification:

  • Classification Detection : Detects the category of an image. Use this model when you need to classify images. Example scenarios: classifying product models, checking if specific screw holes are installed correctly, diagnosing diseases from X-rays.

    

• Detecting anomalies or surface defects on objects:

  • Unsupervised Defect Segmentation : Detects the mask of abnormal areas in an image. Use this model when you need to detect abnormal regions in an image. Example scenarios: detecting surface defects on parts, soldering defects, scratches on lithium batteries.

    

  • Supervised Defect Segmentation : Detects the type and mask of abnormal areas in an image. Use this model when you need to detect and classify abnormal areas in an image. Example scenarios: detecting multiple types of anomalies on part surfaces, ensuring components on a chip are installed correctly.

    

• Detecting text in images:

  • OCR : Detects text in images. Use this model when you need to extract text, letters, or symbols from an image.