Cascaded Modules Commonly Used for AI-Based Quality Inspection
This topic introduces common cascaded modules in AI-based quality inspection and provides example projects for practice.
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Object Detection–Defect Segmentation (Click to download the example project)
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Feature: Position the to-be-detected objects in an image and then detect defects.
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Applicable scenarios: There are many objects to be detected in the original image, and the position and number of objects are random; the shapes of defects vary.
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Defect Segmentation–Defect Segmentation (Click to download the example project)
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Feature: The Defect Segmentation module segments the region to be detected and the background, and then the Defect Segmentation module performs defect detection on the extracted region.
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Applicable scenarios: Complex background, small or inconspicuous defects. The to-be-detected region should be extracted before fine defect detection.
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Text Detection–Text Recognition (Click to download the example project)
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Feature: The Text Detection module quickly locates and extracts text areas in images, reducing background and angle interference. The Text Recognition module identifies characters within the images. The Text Recognition module cannot be cascaded with other modules.
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Applicable scenarios: complex backgrounds and different text orientations.
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