Recognizes two-dimensional objects using a powerful AI-based engine and two methods, one based on color analysis and the other relying on neural networks
| Version | 1.0.6 |
| Updated | October 7 2022 |
| Developer |
GSA
N/A
N/A
|
| User Rating |
93
4.1
|
| Original File Size | 16.8 MB |
| Downloads | 368 |
| Systems | Windows All |
| Category | Multimedia |
GSA Object Counter is designed to recognize two-dimensional objects in live camera streams or images. It features an advanced AI-based object recognition engine that relies on two methods to be able to carry out its mission, namely neural networks and color analysis.
Upon launch, you are greeted by a window that features an XP-like skin. While this is the default looks of GSA Object Counter, please keep in mind that you can change the appearance of the GUI at any time from the application’s options.
There are three preview areas in GSA Object Counter. The first displays the live image, the second shows the original image, while the last reveals the time-shifted instance. The scale mode can be changed with the click of a button.
As mentioned above, there are two methods to image recognition in GSA Object Counter. The first uses neural networks which, combined with the AI-based engine, allows you to assig new objects to trained object groups. This method is recommended for objects with different shapes.
The second method relies on color analysis and, evidently, is suitable for objects with the same shape, but different colors.
Regardless of your choice, there are a few common settings that provide control over the application’s behavior. For instance, you can set the similarity level, set the pixel deviation level, change the time interval, and so on. Also, the object size can be limited by the number of pixels.
GSA Object Counter Crack delivers automatic recognition of 2D objects, with configurable triggermechanisms and two methods to use, both relying on artificial intelligence. Additionally, it comes with monitoring of a defined image area, image filters and customizable output results.
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