AI Lab.
The Easy Way to Create AI Models.
Train, optimize, execute: Create AI models efficiently and seamlessly with the AI Lab. The cloud-based training environment is intuitive to use – ideal for AI users of all experience levels. In combination with the uniVision ecosystem, you can use the strengths of AI and rule-based methods for maximum flexibility in your image processing application.
Maximum User-Friendliness and Intuitive Operation h2>
- Seamless connection to wenglor machine vision hardware – you can quickly and easily upload your image-based training data to the cloud via the weHub connection tool.
- Efficient data management in the cloud – manage multiple data sets and start building AI models straight away.
- Intuitive operating concept – working in the AI Lab means consistent interaction patterns and logical workflows. Get started straight away – without time-consuming training.
Cloud Computing and Scalable User Management h2>
- The cloud architecture gives you flexible access to the AI Lab, allowing projects to continue anytime, anywhere.
- Scalable working – the sophisticated user management allows you to edit data sets and parts of them simultaneously by different users.
- Cloud backup – in the cloud, your data is doubly secured and thus better protected against hardware failures than locally. If necessary, previous data statuses can be easily restored, e.g. after accidental deletion.
Extraordinary Performance h2>
Tracing AI Models for Targeted Optimization h2>
- The integrated heatmap function, AI input image and score values support traceability to help understand your AI model.
- The AI Lab offers you opportunities to optimize your AI model in the best possible way with automatic validation and review function.
Working in the AI Lab Means Taking Advantage of the AI Loop
uniVision 3 in the AI Loop: Capture Image Data and Execute AI Models Locally on Machine Vision devices h3>
As an ecosystem for wenglor machine vision hardware, the uniVision 3 image processing software combines rule-based image processing with AI. It offers a comprehensive toolbox and interfaces.
- Direct recording of training data: Image data is captured directly with the machine vision product and uploaded to the AI Lab via weHub
- Easy AI model integration: AI models from the AI Lab can be easily imported via weHub and deployed in uniVision 3. The AI models can be directly integrated and executed via the “Image AI” module.
- Heatmap display: In addition to the score values per class and the AI model prediction, the heatmap shows which image areas the AI model used in its decision. It is a central tool for better understanding and interpreting the results and evaluating the quality of the AI model.
- Numerous standard interfaces: Results can be output directly via standard network-based interfaces or IOs, enabling easy integration into any type of system.
weHub in the AI Loop: Device Discovery and Connection Tool between Local Network and Cloud h3>
The weHub software runs on a separate PC and performs two central tasks: On the one side, it automatically detects wenglor machine vision devices in the local network and makes it possible to carry out all relevant device settings directly; on the other side, it serves as a connection tool between the AI Lab and the local network.
- Automatic image upload: Images are uploaded directly to the AI Lab from the uniVision platform for AI model training.
- Buffer function: If there is no internet connection, data is stored temporarily.
- Deployment: AI models can be downloaded directly from the AI Lab to the uniVision platform.
Benefits of Combining Rules-Based Image Processing and AI Modules
- Efficient pre-processing directly in the system: Rule-based tools such as “Regions”, “Position tracking” or “Filters” are used to specifically prepare images for AI training. The tools provide the AI model with only relevant image sections or highlight certain features, enabling more robust and reliable detection.
- Pre-processing during model execution: Rule-based tools can also be used during the execution of the AI model, for example for masking or targeted application of the AI model to specific image areas.
- Post-processing and further processing: The results from the “Image AI” module can be further processed with other uniVision modules. This allows applications to be customized and process reliability to be increased.
- Direct communication with the control: Results are reliably transmitted to plant control via standardized interfaces, reducing initial startup and downtime.
AI Lab Plans – the Right Plan for Every Requirement!
| Free plan | Free+ plan | S plan | M plan | L plan | |
|---|---|---|---|---|---|
| Usable storage | 1 GB | 5 GB | 15 GB | 50 GB | 200 GB |
| Usage term | 3 months | 6 months | 12 months | 12 months | 12 months |
| Training credits | 10 credits | 50 credits | 150 credits | 500 credits | 2,000 credits |
| Costs | Free of charge | Free of charge* | Subject to charge | Subject to charge | Subject to charge |
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Free plan
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|---|---|---|---|
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Usable storage
1 GB
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Usage term
3 months
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Training credits
10 credits
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Costs
Free of charge
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Free+ plan
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Usable storage
5 GB
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Usage term
6 months
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Training credits
50 credits
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Costs
Free of charge*
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S plan
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Usable storage
15 GB
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Usage term
12 months
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Training credits
150 credits
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Costs
Subject to charge
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M plan
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Usable storage
50 GB
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Usage term
12 months
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Training credits
500 credits
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Costs
Subject to charge
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L plan
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Usable storage
200 GB
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Usage term
12 months
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Training credits
2,000 credits
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Costs
Subject to charge
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uniVision AI – License Packages
The uniVison AI license package includes the activation of the following modules:
- “Image AI” module (for AI models from the AI Lab)
- “Image ONNX” module (for AI models in ONNX format)
- For B60 series smart cameras: DNNL031 license
- For MVC series machine vision controllers: DNNL032 license
Because Trust Builds on Security – We Protect Your Data!
Opt for a paid plan and stay in full control of your data!
Two Ways, One Goal: Run AI Models on wenglor Hardware
With the uniVision AI license package, AI models can be run both directly from the AI Lab and in ONNX format directly on wenglor devices – for maximum flexibility in AI model development.
With uniVision AI, your AI models are seamlessly integrated into uniVision. Training can be delivered either end-to-end in the AI Lab or in your own toolchain using common machine learning frameworks such as PyTorch or TensorFlow.
AI Model Training in the AI Lab: “Image AI” Module h4>
Ideal for those who want to leverage the entire AI workflow from a single source.
| Model training | Cloud-based in the AI Lab |
| Data flow | Transfer of images from uniVision to the AI Lab via weHub |
| Transparency | Heatmaps and evaluations for maximum traceability |
| Access | Intuitive user interface – ideal for structured projects without their own machine learning toolchain |
Externally Trained AI Models in ONNX Format: Module “Image ONNX” h4>
Perfect for anyone already training with open-source frameworks AI models.
| Model training | Local or external in own toolchain (e.g. PyTorch, Tensorflow) |
| Interface | Import of AI models in ONNX format (via Github) |
| Transparency | Support for heatmaps (depending on the respective AI model) |
| Integration | Direct execution in uniVision – compatibility and conversion according to documentation |