Image processing apparatus and control method
AssigneeCanon Kabushiki Kaisha
InventorYuuichi Nitto
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Abstract
An image processing apparatus presents a result of performing defect detection on an image captured of an inspection target as case information. The apparatus comprises an acquisition unit that acquires the case information according to first information including an image on which the defect detection is to be performed and a presentation unit that presents the case information acquired by the acquisition unit.
Claims15
An image processing apparatus which presents a result of performing defect detection on an image captured of an inspection target as case information, the image processing apparatus comprising:
- a processor;
- and
- a memory, including instructions stored therein, which when executed by the processor cause the image processing apparatus to:
- (1) acquire the case information according to first information including an image on which the defect detection is to be performed;
- (2) present the acquired case information, wherein the case information includes (a) an image on which the defect detection has been performed and (b) second information used in image processing for performing the defect detection, and wherein the second information includes a learned model and a parameter which have been used in the image processing;
- and
- (3) present the learned model so as to be selectable and a parameter of a selected learned model so as to be settable, and
- (4) present a detection result example corresponding to a set value of the parameter of the selected learned model as the case information,
- wherein the learned model and parameters of the learned model are individually selectable,
- wherein a plurality of types of parameters are variably settable for a single learned model,
- wherein the detection result example is presented for each parameter variably settable for the single learned model,
- wherein the inspection target is a concrete structure, and
- wherein the defect includes at least one of cracking, heaving, and flaking of the concrete structure.
A method of controlling an image processing apparatus which presents a result of performing defect detection on an image captured of an inspection target as case information, the method comprising:
- acquiring the case information based on first information including an image on which the defect detection is to be performed;
- presenting the acquired case information, wherein the case information includes (a) an image on which the defect detection has been performed and (b) second information used in image processing for performing the defect detection, and wherein the second information includes a learned model and a parameter which have been used in the image processing;
- presenting the learned model so as to be selectable and a parameter of a selected learned model so as to be settable, and
- presenting a detection result example corresponding to a set value of the parameter of the selected learned model as the case information,
- wherein the learned model and parameters of the learned model are individually selectable,
- wherein a plurality of types of parameters are variably settable for a single learned model,
- wherein the detection result example is presented for each parameter variably settable for the single learned model,
- wherein the inspection target is a concrete structure, and
- wherein the defect includes at least one of cracking, heaving, and flaking of the concrete structure.
A non-transitory computer-readable storage medium storing a program that causes a computer to execute a method of controlling an image processing apparatus which presents a result of performing defect detection on an image captured of an inspection target as case information, the method comprising:
- acquiring the case information based on first information including an image on which the defect detection is to be performed;
- presenting the acquired case information, wherein the case information includes (a) an image on which the defect detection has been performed and (b) second information used in image processing for performing the defect detection, and wherein the second information includes a learned model and a parameter which have been used in the image processing;
- presenting the learned model so as to be selectable and a parameter of a selected learned model so as to be settable, and
- presenting a detection result example corresponding to a set value of the parameter of the selected learned model as the case information,
- wherein the learned model and parameters of the learned model are individually selectable,
- wherein a plurality of types of parameters are variably settable for a single learned model,
- wherein the detection result example is presented for each parameter variably settable for the single learned model,
- wherein the inspection target is a concrete structure, and
- wherein the defect includes at least one of cracking, heaving, and flaking of the concrete structure.
Dependencies are inferred from the claim text.