- Mech-DLK Installer 2.3.0.zip (3.6 GB)
For instructions on the installation of the software, please access Mech-Mind Docs Site.
CRC Value of Installation Package
Mech-DLK Installer 2.3.0.exe
- Installer CRC32 value: E0B7CE0
- Before using Mech-DLK V2.3.0, please upgrade the graphics card driver to 472.50 or above.
- Optimized the algorithms, and thus significantly improved the speed of model training. Only the optimal model is saved during training, and the training cannot be stopped halfway.
- For modules including Defect Segmentation, Instance Segmentation, and Object Detection, you can do smart labeling by selecting the Smart Labeling Tool, clicking on the objects to label, right-clicking to undo the redundant selection, and pressing Enter to complete the labeling.
- For modules including Instance Segmentation and Object Detection, after labeling with the Polygon Tool, if the selection needs to be modified, you can left-click on the line segment between two vertices to add a vertice, or right-click on a vertice to remove it.
- For modules including Instance Segmentation and Object Detection, you can use the Template Tool to set the selection as a template. The template can be applied by simply clicking on the images. It is suitable for scenarios where there are multiple neatly-arranged objects of the same type in an image, and it improves labeling efficiency.
- Support previewing full images and cropped cell images. Please see Resize and Preview.
- Optimized the Grid Cutting Tool. After cutting the image by the grid, you can select a cell image by checking the box in the upper left corner of the cell image, and you can preview the image by clicking on the button in the upper right corner of the cell.
- Added options for filtering results: “Correct results”, “Wrong results”, “False negative”, “False positive”. Added options for filtering data types: “Labeled as OK”, “Labeled as NG”.
- The deep learning environment is built into the software Mech-DLK, and the models can be trained without a separately installed environment.