The invention relates to an AI training multi-
modal imaging-oriented glass defect
data set acquisition device and method, and aims to solve the problems of inconsistent
imaging quality, complex device structure and incapability of automatically constructing a high-quality multi-
modal data set in the existing glass defect acquisition technology. The device comprises a
darkroom structure, and a
light source regulation and control module, a polarization regulation and control module, a spectrum regulation and control module, a
diffuse scattering regulation and control module, a rotary loading platform and an imaging module which are integrated in the
darkroom structure, and each module is controlled by a
control unit in a coordinated manner; according to the method, a multi-dimensional parameter combination matrix is established, parameters are called in sequence to collect images and bind
metadata, and a structured
data set is output after
image registration and fusion. According to the method, ambient light interference is inhibited through modular
electric control design, the consistency and definition of defect images are improved, differentiated display of multiple types of glass defects is realized, a high-quality multi-
modal data set with optical parameter labels is automatically constructed, and reliable data support is provided for AI defect detection model training.