Inspection🔗
On this topic🔗
Bead Inspection🔗
apply_bead_inspection_model: Inspect beads in an image, as defined by the bead inspection
model.
clear_bead_inspection_model: Delete the bead inspection model and free the allocated memory.
create_bead_inspection_model: Create a model to inspect beads or adhesive in images.
get_bead_inspection_param: Get the value of a parameter in a specific bead inspection model.
set_bead_inspection_param: Set parameters of the bead inspection model.
OCV🔗
close_ocv: Clear an OCV tool.
create_ocv_proj: Create a new OCV tool based on gray value projections.
deserialize_ocv: Deserialize a serialized OCV tool.
do_ocv_simple: Verification of a pattern using an OCV tool.
read_ocv: Reading an OCV tool from file.
serialize_ocv: Serialize an OCV tool.
traind_ocv_proj: Training of an OCV tool.
write_ocv: Saving an OCV tool to file.
Structured Light🔗
clear_structured_light_model: Clear a structured light model and free the allocated memory.
create_structured_light_model: Create a structured light model.
decode_structured_light_pattern: Decode the camera images acquired with a structured light setup.
deserialize_structured_light_model: Deserialize a structured light model.
gen_structured_light_pattern: Generate the pattern images to be displayed in a structured light setup.
get_structured_light_model_param: Query parameters of a structured light model.
get_structured_light_object: Get (intermediate) iconic results of a structured light model.
read_structured_light_model: Read a structured light model from a file.
reconstruct_surface_structured_light: Reconstruct a surface from a decoded structured light setup.
serialize_structured_light_model: Serialize a structured light model.
set_structured_light_model_param: Set parameters of a structured light model.
write_structured_light_model: Write a structured light model to a file.
Texture🔗
add_texture_inspection_model_image: Add training images to the texture inspection model.
apply_texture_inspection_model: Inspection of the texture within an image.
clear_texture_inspection_model: Clear a texture inspection model and free the allocated memory.
clear_texture_inspection_result: Clear a texture inspection result handle and free the allocated memory.
create_texture_inspection_model: Create a texture inspection model.
deserialize_texture_inspection_model: Deserialize a serialized texture inspection model.
get_texture_inspection_model_image: Get the training images contained in a texture inspection model.
get_texture_inspection_model_param: Query parameters of a texture inspection model.
get_texture_inspection_result_object: Query iconic results of a texture inspection.
read_texture_inspection_model: Read a texture inspection model from a file.
remove_texture_inspection_model_image: Clear all or a user-defined subset of the images of a
texture inspection model.
serialize_texture_inspection_model: Serialize a texture inspection model.
set_texture_inspection_model_param: Set parameters of a texture inspection model.
train_texture_inspection_model: Train a texture inspection model.
write_texture_inspection_model: Write a texture inspection model to a file.
Variation Model🔗
clear_train_data_variation_model: Free the memory of the training data of a variation model.
clear_variation_model: Free the memory of a variation model.
compare_ext_variation_model: Compare an image to a variation model.
compare_variation_model: Compare an image to a variation model.
create_variation_model: Create a variation model for image comparison.
deserialize_variation_model: Deserialize a variation model.
get_thresh_images_variation_model: Return the threshold images used for image comparison by a variation
model.
get_variation_model: Return the images used for image comparison by a variation model.
prepare_direct_variation_model: Prepare a variation model for comparison with an image.
prepare_variation_model: Prepare a variation model for comparison with an image.
read_variation_model: Read a variation model from a file.
serialize_variation_model: Serialize a variation model.
train_variation_model: Train a variation model.
write_variation_model: Write a variation model to a file.