Release Notes for HALCON 19.11 Progress

• The define for the error code 7824 ("DL: Invalid instance type") has been renamed from H_ERR_DL_DETECTOR_INVALID_TYPE to H_ERR_DL_DETECTOR_INVALID_INSTANCE_TYPE. Applications using this define must be adapted. More information.
• The minimum requirements for deep learning on NVIDIA GPUs have been changed. Now, an NVIDIA driver supporting CUDA 10.1 is required. cuBLAS has been split to two libraries, namely cuBLAS and cuBLASLt. The HALCON installer has been extended to install both libraries. Further, the cuDNN library shipping with HALCON has been updated to 7.6.1. More information.
• Support for deep learning inference on 32-bit Windows has been removed. Further, the extra library hcpudnn.so/.dylib/.dll has been removed and is not needed anymore. More information.
• HALCON's camera models for perspective line scan cameras now support the polynomial distortion model. As a result of this change, the camera model type string 'line_scan' has been replaced by 'line_scan_division'. The old camera type string 'line_scan' is still supported as input to provide backward compatibility. However, applications should be modified to use 'line_scan_division' instead of 'line_scan'. In particular, programs that test for 'line_scan' in a camera parameter tuple that has been output by HALCON must be rewritten to test for 'line_scan_division'. Furthermore, the procedure gen_cam_par_line_scan has been deprecated. It should be replaced by a call to the new procedure gen_cam_par_line_scan_division. More information.
• As the pretrained deep learning models used in semantic segmentation have been changed, other training results than before must be expected. Although the new models perform better in all our tested application cases, if you have chosen very specific training parameters for the old models, you might need to optimize those parameters again for the new models. More information.
• The operators open_file, close_file, fread_char, fread_string, fread_line, fnew_line, and fwrite_string moved from chapter File/Text to File/Access. Further, the corresponding HDevelop example programs moved from the directory hdevelop/File/Text to the directory hdevelop/File/Access. More information.
• Amongst others, a fix for read_texture_inspection_model increases the texture inspection file version. Therefore, models written with HALCON 19.11 cannot be used with older HALCON versions. More information.
• triangulate_object_model_3d with Method set to 'xyz_mapping' or 'greedy' now only returns points that are actually used in the output triangulation. Attributes attached to points get thinned out accordingly. The attributes 'lines' and 'polygons' are not copied to the output. To obtain the old behavior, e.g., to return all input points, set the GenParamName 'greedy_output_all_points' or 'xyz_mapping_output_all_points' to 'true'. Alternatively, you can use the old point indices, which are stored in the triangulated 3D object model as an extended attribute named 'original_point_indices' and which can be queried with get_object_model_3d_params. More information.
• Previously, write_object_model_3d wrote all user added attributes as floats when choosing FileType 'ply'. This behavior has been changed such that all user added attributes are now written as doubles. More information.
• Amongst others, a fix for write_texture_inspection_model increases the texture inspection file version. Therefore, models written with HALCON 19.11 cannot be used with older HALCON versions. More information.
• As the surface-based matching has been extended to be able to calculate a view-based score during the matching and pose refinement step, the interface of the procedure dev_display_surface_matching_results has been extended by the new parameter VisibilityTrained to support the view-based score. More information.
• Extending the functionality of the deep learning model led to changes in the signatures of the following private procedures:
  • dev_display_update_train_dl_model
  • prepare_image_lists
  During this process, parameters have been renamed, which can lead to incompatibilities when running the procedures by the HDevEngine. The following procedures are affected:
  • create_dl_preprocess_param,
  • create_dl_preprocess_param_from_model,
  as well as the following private procedures:
  • get_next_window, and
  • open_next_window.
  More information.
• The interfaces of the procedures disp_menu_ext and inspect_normal_direction are extended by the parameter 'WindowScaling' to scale the text according to the user's setting. More information.

Assistants

Code Export

GUI

IDE

Procedures

Miscellaneous

Assistants

GUI

Help

IDE

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Miscellaneous

New HDevelop Example Programs

Selected New Functionality

Bug Fixes

• If the maximum number of subthreads has been set to a value greater or equal to 64 via the Preferences dialog (Menu > Edit > Preferences > General Options) and more than 64 par_start<> statements were called, HDevEngine and HDevelop hung. This problem has been fixed.
• The method HDevProgram::GetLocalProcedureNames returned all used procedures instead of only local ones. This problem has been fixed.
• In rare cases, JIT compiled procedures could have crashed if they called dev_clear_obj. This problem has been fixed.

• The operators binocular_disparity_ms and binocular_distance_ms have been extended and now offer a coarse-to-fine optimization strategy. The coarse-to-fine strategy requires significantly less memory for large images and large disparity ranges. For example, for an image pair with size 3460x2309 and a disparity range of 800, speedups of over 1000% can be expected. However, the generated disparity images are less accurate for the coarse-to-fine strategy than for the default approach. Especially in case of sharp disparity jumps, the discontinuities are preserved less accurately. Furthermore, it is now possible to pass an empty tuple for MinDisparity and MaxDisparity. The respective values are then computed automatically from the passed input images. Moreover, the operators are now interruptible, i.e. they can be canceled in HDevelop. The HDevelop example program hdevelop/3D-Reconstruction/Binocular-Stereo/binocular_disparity_ms.hdev has been extended to highlight the new functionality.
• find_data_code_2d has been accelerated for Data Matrix ECC 200 codes on multi-core systems. It now supports the parallel execution of multiple parameter sets. Thus, a significant speedup can be expected if one or several of the generic parameters 'polarity', 'contrast_tolerance', or 'finder_pattern_tolerance' are set to 'any', or if the values for 'module_gap_min' and 'module_gap_max' differ. This applies in particular if 'default_parameters' is set to 'enhanced_recognition' or 'maximum_recognition' with create_data_code_2d_model or set_data_code_2d_param. Compared to HALCON 19.05 a speedup of
  • 30 to 70% with enhanced settings, and
  • 60 to 240% with maximum settings
  for 2 to 8 threads can be achieved. Please note, that the memory consumption increases with the number of parallel running threads. The number of threads can be controlled with the corresponding set_system parameters. In addition, it is possible to disable the Data Matrix ECC 200 specific parallelization by setting the new generic parameter 'specific_parallelization' of find_data_code_2d to 'disable'. Per default, 'specific_parallelization' is set to 'enable'.
• The x86 CPU inference for deep learning has been rewritten. The extra library hcpudnn.so/.dylib/.dll has been removed and is not needed anymore. Furthermore, support for 32-bit Windows has been removed. The new inference is faster in some cases; especially object detection is faster by up to 400% in some cases. Note that this change affects the compatibility. Read more.
• gray_erosion_rect, gray_dilation_rect, gray_opening_rect, gray_closing_rect, gray_erosion_shape, gray_dilation_shape, gray_opening, and gray_closing_shape with parameter 'MaskShape' set to 'rectangle' are now faster for 'uint2' images on Intel compatible processors that support SSE2 or AVX2, depending on the image size and mask dimensions.
  In particular, the following speedups can be expected for a 1600x1200 image compared to the previously available SSE2 implementation:
  

  MaskHeight x MaskWidth	Morphological operation	Speedup without Parallelization and with SSE2 (Windows/Linux)	Speedup without Parallelization and with AVX2 (Windows/Linux)	Speedup with 8/2-Thread Parallelization and with SSE2 (Windows/Linux)	Speedup with 8/2-Thread Parallelization and with AVX2 (Windows/Linux)
  3x3	erosion/dilation	10%/5%	85%/100%	150%/80%	160%/160%
  5x5	erosion/dilation	5%/5%	160%/195%	115%/50%	190%/275%
  7x7	erosion/dilation	15%/12%	205%/230%	100%/45%	265%/290%
  9x9	erosion/dilation	10%/7%	185%/203%	85%/30%	200%/270%
  11x11	erosion/dilation	3%/ -5%	120%/125%	25%/15%	85%/135%
  13x13	erosion/dilation	5%/ 0%	145%/160%	60%/15%	140%/160%
  1x3	erosion/dilation	100%/145%	105%/150%	100%/145%	105%/150%
  3x1	erosion/dilation	90%/170%	105%/140%	90%/170%	105%/140%
  1x11	erosion/dilation	3%/30%	5%/40%	3%/30%	5%/40%
  11x1	erosion/dilation	-5%/3%	-5%/3%	-5%/3%	-5%/3%
  3x5	erosion/dilation	60%/75%	65%/75%	60%/75%	65%/75%
  5x3	erosion/dilation	60%/70%	65%/90%	60%/70%	65%/90%
  3x3	opening/closing	-5%/0%	50%/85%	80%/70%	80%/110%
  5x5	opening/closing	-4%/0%	120%/185%	90%/45%	120%/190%
  7x7	opening/closing	5%/5%	165%/220%	80%/30%	150%/255%
  9x9	opening/closing	4%/5%	155%/200%	70%/35%	180%/250%
  11x11	opening/closing	-5%/ -5%	105%/130%	15%/10%	70%135%
  13x13	opening/closing	-4%/0%	130%/160%	40%/15%	105%/175%
  1x3	opening/closing	80%/100%	75%/100%	80%/100%	75%/100%
  3x1	opening/closing	80%/90%	75%/70%	80%/90%	75%/70%

  Note that, previously, values outside the domain have been calculated in the unparallelized case that led to well defined pixel values outside the actual image domain. Now, the image only contains pixel values in the actual domain. Please note that the new SSE2 implementation for filter masks 1xN (e.g., 1x3, 1x5, ...) and for filter masks 3xN (e.g., 3x3, 3x5, ...) can be slightly slower than the old SSE2 implementation.
• The performance of the operators watersheds and watersheds_threshold has been improved for images of type 'real'. watersheds is now up to 35% faster, watersheds_threshold is up to 33% faster.
• The pretrained deep learning models used in semantic segmentation have been significantly improved:
  • dl/pretrained_dl_segmentation_compact.hdl
  • dl/pretrained_dl_segmentation_enhanced.hdl
  Inference speed is improved by 30-45% on GPUs, 90-190% on CPUs, and 90% on Arm®. Additionally, the training is faster and leads to improved results in all our tested application cases. Furthermore, please note that the minimal allowed input image size of the "enhanced" network has been lowered from 81 to 47 pixels in width and height. Note that this change affects the compatibility. Read more.

3D

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Calibration

Data Code

Deep Learning

File

Miscellaneous

Morphology

Parallelization

Segmentation

System

XLD

3D

Bar Code

Calibration

Data Code

Deep Learning

Feature

File

Filter

Graphics

Inspection

Matching

Miscellaneous

OCR

Region

System

XLD

• Triggering error 4056 ("Object-ID is NULL (0)") by calling a HALCON operator from the C or C++ language interfaces with an invalid object could have also invalidated a handle created by the immediately preceding operator. This problem has been fixed.

• Triggering error 4056 ("Object-ID is NULL (0)") by calling a HALCON operator from the C or C++ language interfaces with an invalid object could have also invalidated a handle created by the immediately preceding operator. This problem has been fixed.
• On Linux and macOS systems, the vtable of the HSerializeItem class of the C++ language interface was not exported. This problem has been fixed.

• HSmartWindowControlWPF has had a memory leak when the control was added and removed dynamically. This problem has been fixed.
• Within the HALCON/.NET SetFullImagePart method and the dev_display implementation within the hrun program, the Height/Width arguments for the set_part operator were exchanged. This problem has been fixed.

• The C language interface created for a HALCON extension package did not properly initialize output parameters, which could have led to crashes. This problem has been fixed.

• The HALCON Variable Inspect Extension for Visual Studio can now be used with student licenses.

• The extension package example "halconuser" now contains examples of how to define custom handle types and how to create and use the handles of such a custom type. This covers the previous extension package example "userhandle", which has been removed from the Linux installation.

• The memory benchmarks generated by the program hbench with option -mem produced incorrect results for HALCONARCH=aarch64-linux or armv7a-linux. This problem has been fixed.