Control method for controlling system and system
A control method for controlling a system including an imaging apparatus and a processing apparatus having a learning model to which image data is input includes capturing a first workpiece using the imaging apparatus set to a first imaging condition, thereby obtaining first image data, performing machine learning on the learning model using the first image data as supervised data, obtaining second image data using the imaging apparatus set to the first imaging condition, inputting the second image data to the trained learning model and making an estimation regarding a second workpiece based on the second image data, in a case where an accuracy of the estimation is lower than a predetermined value, obtaining third image data using the imaging apparatus set to a second imaging condition different from the first imaging condition, and performing machine learning on the learning model using the third image data as the supervised data.
1 . A system comprising:
an imaging apparatus; and
a processing apparatus having a learning model to which image data captured by the imaging apparatus is input, the processing apparatus configured to:
perform machine learning on the learning model using, as supervised data, first image data obtained by capturing a first workpiece using the imaging apparatus set to a first imaging condition while changing a position of the first workpiece relative to the imaging apparatus;
input, to the trained learning model, second image data obtained by capturing a second workpiece different from the first workpiece using the imaging apparatus set to the first imaging condition while changing a position of the second workpiece relative to the imaging apparatus and make an estimation as to whether the second workpiece has a defect based on the second image data; and
in a case where an accuracy of the estimation as to whether the second workpiece has a defect is lower than a predetermined value, perform machine learning on the learning model using, as the supervised data, third image data obtained by capturing a third workpiece using the imaging apparatus set to a second imaging condition different from the first imaging condition while changing a position of the third workpiece relative to the imaging apparatus,
wherein the first and second imaging conditions are shutter speeds.
2 . The system according to claim 1 , wherein the shutter speed in the second imaging condition is faster than the shutter speed in the first imaging condition.
3 . The system according to claim 1 , further comprising:
a sensor; and
a trigger generation circuit configured to transmit an image capturing trigger signal to the imaging apparatus,
wherein, in a case where the sensor detects that the first workpiece is present in a predetermined range, the sensor outputs a signal to the trigger generation circuit, and
wherein the imaging apparatus captures the first workpiece based on the image capturing trigger signal output from the trigger generation circuit based on the signal.
4 . The system according to claim 3 , wherein the trained learning model outputs information indicating the estimation as to whether the second workpiece has a defect.
5 . The system according to claim 4 , further comprising a robot,
wherein, in a case where the estimation as to whether the second workpiece has a defect indicates that the second workpiece has a defect, the robot moves the second workpiece.
6 . The system according to claim 4 , further comprising a programmable logic controller (PLC) to which the information indicating the estimation as to whether the second workpiece has a defect is transmitted from the trained learning model,
wherein the processing apparatus and the PLC are connected together wirelessly, and
wherein the sensor and the trigger generation circuit are connected together by wire.