Deep Learning Tool: MVTec Software

The easy way into Deep Learning with MVTec Software

Labeling training data is the first crucial step towards any deep learning application. The quality of this labeled data plays a major role when it comes to the application's performance, accuracy, and robustness.

With the Deep Learning Tool, you can easily label your data thanks to the intuitive user interface – without any programming knowledge. This data can be seamlessly integrated into HALCON to perform deep-learning-based object detection and classification. For classification projects, you can also train and evaluate your model in the Deep Learning Tool.

To help you label data for HALCON's semantic segmentation, we provide Deep Learning Helpers for download.

The Deep Learning Tool offers

A fast path to the complete Deep Learning solution
An intuitive user interface
Active support for the optimization of the trained networks
Easy integration into the MVTec portfolio
Full control over your own data

Free Download

Working with the Deep Learning Tool

Labeling

for Object Detection

With object detection, labeling is done by drawing rectangles around each relevant object and assigning these rectangles to the corresponding classes. Depending on the project requirements, the user can label his data with either axis-parallel or oriented rectangles.

Labeling of screws of different sizes

animated screenshot of the deep learning tool which shows labeling for object detection — Please click on the image to see the animated GIF.

for classification

Labeling for classification is done by simply importing the images and assigning them to a class. If the images are stored in appropriately named folders, they can also be labeled automatically during import.

Labeling different color toothbrush heads

animated screenshot of the deep learning tool which shows labeling for classification — Please click on the image to see the animated GIF.

Training for classification

Users can set all important parameters and perform training based on their labeled data.

Progress of the training process

Please click to see the animated GIF. — Please click on the image to see the animated GIF.

Evaluation for classification

Users can evaluate and compare their trained networks directly in the tool. The evaluation section provides information on model accuracy, including a heatmap for the predicted classes of all processed images, as well as an interactive confusion matrix to help detect misclassifications. Users can also calculate the estimated inference time per image and export the evaluation results as a single HTML page for documentation purposes.

Evaluation of the trained networks

Seamless integration into the MVTec product portfolio

The Deep Learning Tool seamlessly integrates into the MVTec product portfolio with HALCON and MERLIC and serves as the core of your Deep Learning application.

Acquire your images and preprocess them with HALCON or MERLIC if necessary. After labeling, training as well as evaluation in the Deep Learning Tool, deploy your trained network in the respective runtime environment.