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I am quantizing my yolov5 model with tflite using the following code :
import tensorflow as tf saved_model_dir ='path2_saved_model' converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir) converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.representative_dataset = representative_dataset converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8] converter.inference_input_type = tf.int8 # or tf.uint8 converter.inference_output_type = tf.int8 # or tf.uint8 tflite_quant_model = converter.convert()
however when I try to run detect, it expects the input image to be int8, how can I solve this issue, thank you in advance!
The text was updated successfully, but these errors were encountered:
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I am quantizing my yolov5 model with tflite using the following code :
import tensorflow as tf
saved_model_dir ='path2_saved_model'
converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.representative_dataset = representative_dataset
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
converter.inference_input_type = tf.int8 # or tf.uint8
converter.inference_output_type = tf.int8 # or tf.uint8
tflite_quant_model = converter.convert()
however when I try to run detect, it expects the input image to be int8, how can I solve this issue, thank you in advance!
The text was updated successfully, but these errors were encountered: