MVTEC Deep Learning Tool 23.04 Full Version x64 windows 深度学习工具dlt-23.04完整版

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MVTEC Deep Learning Tool 23.04 Full Version x64 windows 深度学习工具dlt-23.04完整版

文件名: dlt-23.04.zip
文件大小: 2281498070 字节 (2.12 GB)
修改日期: 2023-04-19 21:23
MD5: 6fbdc9581a341978c53ce8315dd194f3
SHA1: e6a32ff2b233b14603f3e5e62b82e2bbc1004608
SHA256: f6e8ce3094ee6dc086dd5e70356137d2ba8b5884d5f89c0aa183828195b0ebba
CRC32: b499b6a9

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VERSION 23.04NEW FEATURES

• As of this release, the DLT supports training and evaluation for Object Detection and Instance Segmentation for the models provided by HALCON.
• The quick help on the Split, Training, and Evaluation pages has been improved. Now, instead of the integrated panel, the quick help opens in a window. The respective quick help can be accessed via icons next to a section header or via the Quick Help menu entry.
• When changing the evaluation settings, it can happen that the displayed evaluation result is not valid anymore. In this case, now a warning box is shown, which offers to reset the parameters to the previously used values or to update the evaluation with the new parameters. Inconsistent parameters are displayed in orange color.
• The evaluation can now be run on HALCON AI2-Interfaces for OpenVINO™ and TensorRT™ if an appropriate device is available.
• Adding a comment to a training or editing it is now possible on both the Training and Evaluation pages. The text fields to enter comments have been replaced by buttons opening dedicated dialogs.
• It is now possible to reset the DLT window to the initial window size (1280x800) via the shortcut Shift+F11.
• The Evaluation page has been redesigned to improve clarity and allow more information to be presented.
• Users can now press Ctrl+F to search the images on the Gallery page via the quick text filter functionality.
• Except for Anomaly Detection, the training options of all project types now offer selecting the solver used to minimize the value of the total loss function (Adam or SGD).
• The pseudo class name “No label”, used to display unlabeled images or statistics about these images, has been renamed to “Unlabeled images”.
• The term “label” has been changed to “instance” to reflect the broader range of deep learning methods.
• The DLT has been extended by an additional filter criterion. The images can now be filtered based on the image comment. Further, the quick text filter additionally now considers the image comment.
• The DLT has been extended with the possibility to add a comment to every image in the dataset on the Image page.
• In GC-AD projects, the Postprocessing dialog on the Evaluation page now offers the option to restrict the domain of the inference images by axis-aligned rectangles.
• The submodels of anomaly detection trainings (GC-AD Combined, Global, Local) can now be exported individually.
• The evaluation report now contains further information about the used postprocessing parameters for anomaly detection projects.
• The functionality to export trained models and reports is now located on a separate Export page.
• The Training page has been extended with a dialog that allows adapting the network and preprocessing parameters and visualizing their impact on the training images.
  

RESOLVED ISSUES AND IMPROVEMENTS

• If there are no images in a project, the Image and Review pages are disabled. This did not happen if all images were removed from the project. This problem has been fixed.
• The shipped pill bags example for object detection contained an invalid split. This problem has been fixed by removing the split.
• If an image that is hidden by the filter settings was about to be displayed via the “Show Image” context menu on the Evaluation page, the selected page (Gallery, Image, or Review) was displayed but not the requested image. This problem has been fixed. Now, the image filter is deactivated before an image hidden by the filter is displayed.
• When a split of a finished training was removed, the training could not be reset. This problem has been fixed.
• In Anomaly Detection projects, when resetting the classification threshold in the postprocessing dialog, an old value was displayed. This problem has been fixed.
• When all criteria were removed from an existing image filter in the Edit Image Filter pane, this change could not be accepted via the OK button. This problem has been fixed.
• In the report, now the optional comment for a training is placed right above the training parameters. Further, now the optional split comment is shown in the report.
• Sometimes, Asian characters were not displayed well. This problem has been fixed by improving the font rendering.
• If there are no images due to the filter settings, the Image and the Review pages are disabled. The tooltips of the corresponding page buttons were wrong and have been improved.
• The score histogram in the report had a less precise visualization than in the Deep Learning Tool. This problem has been fixed.
• On the Image page, editing the angle of an oriented instance with the spinbox did not work properly. This problem has been fixed.
• The delete button for labels sometimes was outside the visible area. This problem has been fixed.
• The settings on the Evaluation page sometimes remained disabled after evaluation had finished. This problem has been fixed.
• The documentation did not mention exactly which earlier HALCON Steady versions support trained classification models. This problem has been fixed. The earliest supported version is HALCON 20.11.2 Steady.
• If the display of bounding boxes was activated on the Image page for instance-based segmentation projects, bounding boxes were also activated in the postprocessing dialog in anomaly detection projects. This problem has been fixed.
• The functionality to clone an image filter was broken and displayed an error dialog. This problem has been fixed.
• Very low learning rates in a learning rate strategy could not be deleted instantly. This problem has been fixed.
• When an image filter is created and the user does not set a name, the filter automatically gets a name that is generated from the first criterion. If afterward the first criterion was changed, the generated name was not adapted accordingly, so that it did no longer match the actual expression. This problem has been fixed. As long as the user does not set the filter name manually, the name is adapted with every change of the expression.
• The DLT allowed increasing the batch size to a larger value than the training set size. Further, the DLT did not adapt the base value of the learning rate schedule if the user did not hit enter, but only clicked the plus button. These problems have been fixed.
• When the DLT ran out of memory during training of an anomaly detection model, the error message asked to adapt the batch size. However, the batch size cannot be changed in the case of a GC-AD project. This problem has been fixed by correcting the error message.
• When editing a filter, the operation was not properly displayed. This problem has been fixed.
• When changing the HDICT file to be imported in the New Project dialog, the methods were not correctly enabled and disabled. This problem has been fixed.
• After exporting the evaluation report, it was no longer automatically displayed in a browser. This problem has been fixed.
• Showing the bounding boxes of the instances when editing a specific instance mask has been disabled.
• The appearance of leftover project files on the Project page has been improved.
• When dragging files to the DLT, the cursor icon did not always correctly indicate whether this was allowed. This problem has been fixed.
• During the import of a HALCON dictionary, the path sometimes changed unexpectedly when editing the image directory. This problem has been fixed.
• The model parameters for creating an instance-based detection model can now be estimated by analyzing the training data set.
• The DLT crashed when using a touch screen on the Image page. This problem has been fixed. The label area now ignores touch events. However, it is now possible to create and edit labels with a pen.
• When using the Smart Label Tool in an instance segmentation project, the user did not get a visual feedback where the foreground seed point was placed. This problem has been fixed.
• Importing an OCR recognition DLDataset in the simple format requires a valid image directory before loading the labels. The DLT did not enforce this requirement. This problem has been fixed.
• The DLT did not handle the export of Deep OCR recognition DLDatasets in the simple format correctly. This problem has been fixed. The exported dataset now contains the word strings exclusively in the label_custom_data key.
• It was possible to remove an opened project from the recent project list. This problem has been fixed.
• On the Image page, when reducing the size of the zoom pane on the right, the controls could still be used although they were covered by the label list. This problem has been fixed.
• Continuously moving selected regions with a pressed cursor key was broken. It was necessary to press and release the key for every single moving step. This problem has been fixed.
• Generated splits did not always match the predefined distribution comprehensibly. This problem has been fixed.
  

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