I built a custom model for classifying images of cars using Tensorflow and Keras, to use it for building a Snap lens powered by machine learning. Lens Studio only accepts quantized models; the model had to go through the quantization process using the TFLite module.
However, the problem is that the model passed into Lens Studio is unable to function properly. It only displays classification results for the first time after its initiation; then the results (and even the probability numbers behind classification) remain static despite image/video changes.
Any tips on how to solve this issue would be appreciated. The configurations for input image setups remain identical as the provided template by Snap.
