Integration of multiple intelligent identification modules, including appearance attribute identification (e.g. size, colour, etc.), barcode reading and label content identification, label defect identification (e.g. defective label printing, blurring, disconnection, poor screen printing, etc.)

The system integrates multiple intelligent identification and detection modules; the deep learning algorithm model has high accuracy; it supports customers' rapid and highly customised requirements; the system can be docked to achieve the "four no's" and can be deployed efficiently and quickly; it is versatile and stable, and it has been applied in a number of the world's top 500 enterprises.

As product quality standards and after-sales service requirements are getting higher and higher, product appearance quality inspection (such as size, colour, etc.), barcode reading, label content OCR recognition, and related defect detection (such as product surface defects, label printing errors or poor print quality, etc.) is getting more and more attention. Existing production lines are mostly manual inspection, low efficiency, poor reliability, resulting in unstable product quality, high defective rate, production labour and after-sales costs, brand image damage and a series of problems. HP printer project is the appearance of the printer label inspection, mainly to detect the colour accuracy, handwriting clarity, whether the content is correct, whether the label is pasted in accordance with the specified locations, label printing errors or poor print quality and other defects. Performance indicators fully meet customer requirements, in several key indicators of performance beyond customer expectations.