Nozzle inspection unit and substrate treatment apparatus including the same

A nozzle inspection unit comprising:

• a controller configured to:
• collect a plurality of image data related to nozzles;
• classify the plurality of image data according to predefined classes;
• generating, after classifying the plurality of image data, a plurality of merged image data by:
• first merging a first number of good image data related to a normal nozzle from among the plurality of image data with a second number of defect image data related to a defective nozzle from among the plurality of image data to obtain a first merged image data of the plurality of merged image data, the second number being smaller than the first number;
• and
• generating remaining ones of the plurality of merged image data besides the first merged image data by duplicating and rotating the first merged image data at a third number of random rotation angles such that each of the remaining ones of the plurality of merged image data besides the first merged image data is the first merged image data rotated at one of the third number of random rotation angles;
• train the plurality of merged image data after the plurality of merged image data is generated;
• and
• generate a plurality of final image data from the plurality of merged image data based on a training result of the training of the plurality of merged image data,
• wherein the controller is further configured to:
• generate a number of the final image data greater than a reference number from a number of the defect image data smaller than the reference number,
• obtain fake image data similar to the merged image data by training the merged image data, wherein the controller obtains the fake image data using a GAN, and
• remove the fake image data similar to the merged image data from the plurality of merged image data and generates the final image data based on the remaining merged image data.

A substrate treatment apparatus comprising:

• a support configured to support a substrate while the substrate is treated;
• an inkjet head unit including a plurality of nozzles and configured to jet a substrate processing liquid onto the substrate using the nozzles;
• a gantry unit having the inkjet head unit installed thereon and configured to move the inkjet head unit on the substrate;
• and
• a controller configured to inspect the nozzles,
• wherein the controller is configured to:
• collect a plurality of image data related to the nozzles;
• classify the plurality of image data according to predefined classes;
• generating, after classifying the plurality of image data, a plurality of merged image data by:
• first merging a first number of good image data related to a normal nozzle from among the plurality of image data with a second number of defect image data related to a defective nozzle from among the plurality of image data to obtain a first merged image data of the plurality of merged image data, the second number being smaller than the first number;
• and
• generating remaining ones of the plurality of merged image data besides the first merged image data by duplicating and rotating the first merged image data at a third number of random rotation angles such that each of the remaining ones of the plurality of merged image data besides the first merged image data is the first merged image data rotated at one of the third number of random rotation angles;
• train plurality of merged image data after the plurality of merged image data is generated;
• and
• generate a plurality of final image data from the plurality of merged image data based on the training result.