2.6 QR Code Recognition
0. Introduction to [QR Recognition]
The [QR Code Recognition] model allows users to train specific QR codes and create a customized QR code recognition model.
The recognition principles of [QR Code Recognition] and [Tag Recognition] are similar, as both use visual markers to identify specific information.
QR codes are primarily used for information storage and retrieval, whereas tags are mainly used for object recognition.
As the amount of stored data in a QR code increases, its visual complexity also increases, making it more difficult for the HUENIT AI Camera to recognize compared to tags.
1. How to Train the [QR Recognition] Model
When launching [QR Recognition] for the first time, an empty screen may appear if no QR code is detected.
When a detectable QR code is placed in front of the camera, a white square will appear around it.
If a white square appears around the QR code to be trained, tap the touchscreen to begin training.
Once training is complete, scan the same QR code again to verify that the assigned ID appears on the screen.
The [QR Recognition] model supports up to 10 unique QR code IDs.
The same QR code can be assigned multiple IDs, so careful ID management is required.
2. Completing Model Training
To finalize the [QR Recognition] model training, press and hold the button on the AI Camera for 2 seconds.
If the button is not held down long enough, the system will return to the AI Model Selection screen, requiring the model to be retrained from the beginning.
When the [End Training] pop-up appears, press the button to confirm and finalize training.
✅ After completing training:
You can now test your custom [QR Code Recognition] model.
Verify whether the system correctly recognizes the trained QR codes, ensures the correct QR code data is detected, and maintains the correct training order.
3. How to Save a Trained Model
Once the model has been successfully trained and verified, it can be saved in HUENIT OS. This allows the model to be used later in HUENIT LAB (Software).
Press and hold the button on the AI Camera after training is complete.
Click [Save Model] to store the trained model in HUENIT OS.
If the training results are unsatisfactory, click [Delete & Retrain] to restart the training process.
In [Save Model], choose a storage slot except for the 6th option (Not Saveable).
"Empty Space" indicates an available slot with no saved model.
Slots with existing names already contain trained AI models.
⚠ Warning: Saving a new model in an occupied slot will overwrite and delete the existing model.
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