SDKs for Image Processing with ML
SDKs for easy integration into your own capturing and recognition applications.
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Android, iOS, Windows, Linux, Raspberry OS (ARM 32 & 64)
Xamarin Forms, .NET LTS, .NET MAUI
Plugin structure, which allows the use of different recognition processors. Even your own.
Barcode and QR-Code recognition
ML based license plate and vehicle type recognition with support of the most European countries
Capture images for recognition from any webcam with RTSP and H264 support
Full Multi-Stream and Multi-Threading support. Lightning fast
GPU is supported if the platform supports it
No image compression artifacts, RAW support
Develop before pay
One license per company and not per developer or project
Create your Xamarin Forms application in no time.
Just use our libraries and all the image processing and object recognition happens by itself. If desired, the objects found can even be displayed graphically (overlay).
On Android, the libraries support the operating system's new Camera API, which allows images to be obtained in different resolutions at the same time. This means that the images for displaying on the screen can have a different resolution than those used to recognize the objects. This saves an enormous amount of computing power and battery.
Create your own cross-platform applications for object recognition.
The same application works under different operating systems and processor types. All functions of the libraries can be used independently of the platform and automatically adapt to the operating system so that the maximum performance of the corresponding operating system and processor is always used for processing.
When programming the libraries, special attention was paid to performance and memory consumption, so that even a rather slow processor such as a Raspberry Pi 4 still works quickly under a 32-bit operating system without much graphics support.
Will follow soon.
The same features as Xamarin Forms only rewritten to optimally support .Net MAUI and use the new introduced render technology.
Create your .NET MAUI application in no time. Just use our libraries and all the image processing and object recognition happens by itself. If desired, the objects found can even be displayed graphically (overlay).
On Android, the libraries support the operating system's new Camera API, which allows images to be obtained in different resolutions at the same time. This means that the images for displaying on the screen can have a different resolution than those used to recognize the objects. This saves an enormous amount of computing power and battery.
Why is it always all or nothing and why can't we expand anything ourselves?
This is exactly the question we asked ourselves when analyzing third-party providers.
Our philosophy is completely different:
Only include what you need and allow other developers to extend it.
We have developed a fully modular plug-in framework that allows recognition plug-ins (so-called processors) to be integrated into the image stream in a modular, simple and efficient way and the results obtained to be returned with the results stream.
This means that only what is actually needed is used. This reduces the size of the resulting application and thus saves memory space on the corresponding device.
With our libraries, the developer can choose whether the processors are to be operated sequentially or in parallel. Both modes have their advantages and disadvantages, but this is the only way to take into account the requirements of the application to be created and conserve the resources of the devices.
The barcode and QR code recognition processor recognizes as many codes as possible within an image and decodes them.
This processor makes it possible to recognize and decode several barcodes and QR codes scattered across an image. The developer can use various parameters to influence the recognition, the results and the display of the results.
Depending on the developer's configuration, the results are displayed (e.g. as an overlay).
To improve the recognition of QR codes, a special binarizer has been developed, which enables QR code recognition under special lighting conditions (Impoved DPM Binarizer).
Supported formats:
The license plate recognition processor recognizes the license plate of various European countries and identifies the corresponding vehicle type. The processor is not limited to a single vehicle/license plate. Depending on the image quality and image resolution, several vehicles/number plates are recognized simultaneously.
State-of-the-art ML (machine learning) is used to enable this reliable recognition. The models we use are constantly being expanded and improved by us in order to recognize even more countries and vehicle types even more accurately.
Supported vehicle types:
Supported countries:
CH, DE, GB, DK, A, I, F, B, PL, E, S, FL, CZ, NL, P, SLO
