euDominic

@hobbyquaker wird das Projekt noch aktiv supportet? Selbes Problem bei mir und mit Sicherheit jedem anderen auch. Bitte nicht nur in anderen Projekten Kommentare hinterlassen, sondern auch hier etwas "Rest"...

> > tflite_convert --saved_model_dir=/home/dom/tensorflow/workspace/training_demo/exported-models/tfliteexport/saved_model --output_file=/home/dom/tensorflow/workspace/training_demo/exported-models/tfliteexport/saved_model/detect. tflite --input_shapes=1,300,300,3 --input_arrays=normalized_input_image_tensor --output_arrays='TFLite_Detection_PostProcess','TFLite_Detection_PostProcess:1','TFLite_Detection_PostProcess: 2','TFLite_Detection_PostProcess:3' --inference_type=FLOAT --allow_custom_ops --mean_values=128 --std_dev_values=128 --change_concat_input_ranges=false --allow_nudging_weights_to_use_fast_gemm_kernel=true > > Ops has to be either [int8 or unit8](https://coral.ai/docs/edgetpu/models-intro/#model-requirements). please try with inference_type=QUANTIZED_UINT8...

> unfortunately, that was not the solution either. Neither QUANTIZED_INT8 nor QUANTIZED_UINT8 did any good. I will probably have to go back to TF1 Edge TPU Compiler version 16.0.384591198 Started...

I am also interested in a custom Firmware for the Petkit Eversweet 3 Pro