How to Choose Between the Instance Segmentation Module and the Object Detection Module
Both the instance segmentation and object detection modules can identify objects in images and classify them, but they differ in output format and accuracy. You can choose which to use based on your actual needs. The object detection module can identify the location and class of objects, while the instance segmentation module, in addition to this, can accurately extract the contour of each object and generate precise masks. For common scenarios, you can make your choice based on the following criteria.
Object Shape and Output Contour Accuracy Requirements
When the object has a regular shape and simple contour (such as rectangular, circular, elliptical, etc.), and the project does not require precise contour information or high accuracy for pick points, you can prioritize using the object detection module.
When the object has a complex or irregular shape, and the precision of its geometric contour directly affects the accuracy of picking, the instance segmentation module should be chosen. The module can provide pixel-level contour information to help achieve precise picking.
Positional Relationships Between Objects
When objects are not tightly fitted together or overlapping (allowing for slight occlusion), you can prioritize using the object detection module.
When objects have extensive tight fitting or overlapping, the instance segmentation module should be chosen to accurately distinguish and identify objects through pixel-wise segmentation.
Object Aspect Ratio
When the aspect ratio of the object is small, meaning it is close to a square shape, the rectangular bounding boxes used by the software can accurately fit the contour of the object, as such, it is recommended to choose the object detection module.
For objects that are slender, especially when arranged in a regular pattern, it is recommended to use the instance segmentation module to achieve more precise contour recognition.
Common Case Descriptions
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Example 1: In scenarios where objects with relatively regular shapes are picked up using magnetic suction, the object detection module can be used.
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Example 2: In scenarios where objects have irregular shapes and severe overlapping, and are picked using two-finger grippers, the recognition difficulty is high and precise picking point accuracy is required; therefore, the instance segmentation module is needed.
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Example 3: For slender, tightly packed long-strip objects, accurately identifying the contour of each individual object is challenging, so the instance segmentation module is required.
