IDS peak 2.10.0 / uEye+ firmware 3.34
IDS Peak comfortSDK, genericSDK, IPL, and AFL developer manuals are external documents. Please contact us if you need them.
You can load and run neural network (CNN) in IDS peak Cockpit. You can execute networks for classification as well as for object detection. After image acquisition by the camera, the images are transferred to the AI library in host processing and analyzed. The entire image is used for the analysis. The result is displayed in the camera image in the IDS peak Cockpit.
As the images are processed in the host processing, it is possible to execute both classification and object detection on the same image.
Prerequisite: The CNNs were trained for use with IDS peak. For this purpose, you can use the AI Vision Studio IDS lighthouse.
•Nets for classification have the file extension *.pcla
•Nets for object detection have the file extension *.pdet
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Notes for using AI-assisted image analysis •The inference is executed on the host system and therefore the performance depends on the host system. •The CPU load can be very high depending on the CNN used and the host system. •If you use multiple networks at the same time, the CPU load will be correspondingly higher. •The inference is processed synchronously via the IDS peak comfortSDK interface, i.e. the function only returns after an image has been analyzed. |
Optionally, after installing IDS peak, you find three simple neural networks for testing under "<IDS peak installation directory>/cnn". These networks were created for test purposes and are not intended for productive use.
CNN-name |
Type |
Short desctiption |
|---|---|---|
cats_dogs_classification.pcla |
Classification |
Classifies dogs or cats |
item_classification.pcla |
Classification |
Classifies simple items like pens, car keys, wallets, cameras etc. |
person_detection.pdet |
Object detection |
Detects people |
