Method run

code/train/step5_inference.py:31–41

(self, inputData)

        print(f'Save TFLite model to {self.model_path} successfully!')

    def run(self, inputData):
        # Preprocess the image before sending to the network.
        inputData = np.expand_dims(inputData, axis=0)

        # The actual detection.
        self.interpreter.set_tensor(self.input_details[0]["index"], inputData)
        self.interpreter.invoke()

        # Save the results.
        output = self.interpreter.get_tensor(self.output_details[0]["index"])[0]
        return output
    
    def get_weight(self, data, label_len=37):
        # weight = self.run(data)