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
- 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
- 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.
- Automatic backups – the backup schedule allows you to restore data at a specific time or previous versions of a file, for example if it is accidentally deleted or damaged.
Extraordinary Performance
With the AI Lab, you can also train large data sets and complex AI models. The high-performance computing power enables deep learning for very powerful AI models for image classification and replaces costly local infrastructures.
Tracing AI Models for Targeted Optimization
- 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
Image Capture and Upload
Annotation
Train and Validate
Deployment
The AI Loop enables easy and fast AI modeling. The AI Lab enables efficient data management and AI model training in the cloud, while the uniVision 3 software enables image recording and the high-performance execution of AI models on machine vision products. The workflow is rounded off by the weHub software as a connection tool and for device discovery.
uniVision 3 in the AI Loop: Capture Image Data and Execute AI Models Locally on Machine Vision devices
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
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 without any IP configuration and makes it possible to carry out all relevant device settings directly and, on the other side, 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!
The AI Lab is used on the basis of prepaid plans. Choose the model that suits you best! The plans differ in terms of duration and scope of resources. The training credits can be used flexibly during the active term. You can book plans consecutively or upgrade within a term as needed. Of course, all plans are set up without automatic renewal – completely transparent and without hidden costs.
| 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
|
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
|
Usage term
6 months
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Training credits
50 credits
|
Costs
Free of charge*
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S plan
|
|||
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Usable storage
15 GB
|
Usage term
12 months
|
Training credits
150 credits
|
Costs
Subject to charge
|
|
M plan
|
|||
|
Usable storage
50 GB
|
Usage term
12 months
|
Training credits
500 credits
|
Costs
Subject to charge
|
|
L plan
|
|||
|
Usable storage
200 GB
|
Usage term
12 months
|
Training credits
2,000 credits
|
Costs
Subject to charge
|
uniVision AI – License Packages
For the execution of the AI models created in the AI Lab, the “Image AI” module is available on the relevant machine vision hardware. This is included in the uniVision AI license package.
The uniVison AI license package includes the activation of the following modules:
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
- Device variants of the B60A or MVCA series include the license as standard
Because Trust Builds on Security – We Protect Your Data!
The AI Lab only uses European servers. Automatic backups in the cloud ensure that your data is backed up regularly. Create flexible access restrictions for your images.
Opt for a paid plan and stay in full control of your data!
Opt for a paid plan and stay in full control of your data!
Have you already developed your AI models? You can run these on uniVision 3 with the “Image ONNX” module!
The “Image ONNX” and “Image AI” modules both offer the option of running AI models in uniVision 3 and are included in the uniVision AI license package.
“Image AI” Module vs. “Image ONNX” Module – which AI Module Is Right for Your Application?
| Criteria | “Image AI” module | Module “Image ONNX” |
|---|---|---|
| Model source | AI models trained with the AI Lab | External AI models in ONNX format (e.g. from PyTorch, TensorFlow) |
| Training environment | Cloud-based in the AI Lab | Local or external with its own toolchain |
| Image capture and image upload | Directly from uniVision via weHub to the AI Lab | Manual recording and optional manual upload |
| Storage location for training data | Cloud (AI Lab, EU hosting) | Local at the user |
| Heatmap function | Present | Supported |
| Expert level | Also suitable for AI beginners thanks to intuitive web interface | Requires experience in machine learning and Python programming |
| Execution on devices | AI models optimized for B60 series smart cameras and MVC series machine vision controllers | Observe GitHub documentation on compatibility and conversion of AI models |
| Licensing | Included in the uniVision AI license package | Included in the uniVision AI license package |
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Model source
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AI models trained with the AI Lab
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External AI models in ONNX format (e.g. from PyTorch, TensorFlow)
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|
Training environment
|
|
|
Cloud-based in the AI Lab
|
Local or external with its own toolchain
|
|
Image capture and image upload
|
|
|
Directly from uniVision via weHub to the AI Lab
|
Manual recording and optional manual upload
|
|
Storage location for training data
|
|
|
Cloud (AI Lab, EU hosting)
|
Local at the user
|
|
Heatmap function
|
|
|
Present
|
Supported
|
|
Expert level
|
|
|
Also suitable for AI beginners thanks to intuitive web interface
|
Requires experience in machine learning and Python programming
|
|
Execution on devices
|
|
|
AI models optimized for B60 series smart cameras and MVC series machine vision controllers
|
Observe GitHub documentation on compatibility and conversion of AI models
|
|
Licensing
|
|
|
Included in the uniVision AI license package
|
Included in the uniVision AI license package
|
Powerful Hardware for Optimal Execution of AI Models
The AI models trained in the AI Lab are perfectly matched to wenglor hardware. On the B60 series smart cameras, the adaptation of the AI models to the Neural Processing Unit (NPU) ensures their efficient and fast execution. The multicore processor and Intel® OpenVINO™ acceleration of the MVC series machine vision controllers are ideal for running multiple AI models in parallel as well as using different process instances in complex applications.
