Release Notes

Mech-DLK 2.5.0 now features optical character recognition (OCR) that is realized by cascading the following two algorithm modules:

This feature is usually employed to detect and recognize tiny characters on electronic components, vehicle-related data against complex backgrounds, and serial numbers and lot numbers displayed on the packaging.

Mech-DLK 2.5.0 now features the Unsupervised Segmentation module, which only requires OK images in the training set to achieve pixel-level detection of all known and unknown defects. The trained model can be used to judge whether the image of an object is OK, NG, or Unknown on the basis of set thresholds. Moreover, heat maps are available to show the possible areas with defects.

This module is usually used for industrial quality inspection in scenarios where

In the Text Detection module, the Free Rectangle Tool can be used to draw a rectangle around the text area. It is recommended to select this tool for rectangular text areas.

In the Text Recognition module, the Text Recognition Tool can be used to define the text recognition range and automatically generate the recognition result.

Mech-DLK 2.5.0 now allows to directly label images as OK or NG with the OK/NG Labels. Select an image from the image list and click the OK Label or NG Label on the toolbar. The image will be labeled as OK or NG.

Mech-DLK 2.5.0 now fully supports NVIDIA GeForce RTX 40 Series GPUs for model training and validation.

In Mech-DLK 2.5.0, the floating window of keyboard shortcuts displays the shortcuts by modules for easy and fast search.

Mech-DLK 2.4.1 has added a brand-new cascade mode of modules, which enables the combination of modules to solve deep learning problems in complex scenarios. It should be noted that when the Fast Positioning module is involved, it must be the first module. For example, when you need to detect the positions of defects and classify these defects, you can first add a Defect Segmentation module and then add a Classification module. In addition, when importing data from the previous module, you can select images according to actual needs and configure the import of these images in the Import window.

The Training Center supports the training of models in a queue, which is suitable for scenarios requiring the training of multiple models. With the Training Center, the software can train models in sequence, with no need for manual clicking of Train repeatedly, which can save a huge amount of time.

In the Defect Segmentation module, when you select the Mask Polygon Tool, the mask type can be Mask single image or Mask globally. In addition, you can customize the mask color.

Click in the lower-right corner of the selection region to open the window of keyboard shortcuts.

In the Instance Segmentation and Object Detection modules, auxiliary labeling lines are added for the Rectangle Tool to assist rectangular selection on images.

In the Instance Segmentation and Object Detection modules, a confidence filtering function is added for validation results. You can adjust the confidence to filter the validation results and then evaluate the accuracy of models.

The Classification module is optimized, which leads to faster training convergence and a growth rate of 20% in accuracy under complex scenarios.

Mech-DLK SDK is more stable and easier to use after being restructured. Mech-DLK SDK supports the inference based on the cascaded modules and the switching between different operating hardware. In addition, it provides richer samples for reference.

The defect determination rule in the Defect Segmentation module is optimized. Click here to view the details.

In the Image Adjustment window of the Fast Positioning module, you can translate the image along the X and Y axes. After training, images with objects in specified positions and orientations will be generated, which meet the requirements of more application scenarios.

In the Instance Segmentation and Object Detection modules, after selecting the Template Tool, press and hold the Shift key and scroll the mouse wheel to adjust the angle of the template. You can also set the Rotation angle to achieve the same purpose.