A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
TensorFlow Saved Model format version of the BlendshapeV2 model yields significantly different results from the TFLite Version (face_blendshapes.tflite)
Relevant Log Output
No response
URL or source code for simple inference testing code
import tensorflow as tf
import numpy as np
test_data = np.random.rand((1, 146, 2))
model = tf.saved_model.load("BlendshapesV2/saved_model")
model_sd = model.signatures["serving_default"]
interp = tf.lite.Interpreter("BlendshapeV2/face_blendshapes.tflite")
interp.allocate_tensors()
input_tensor = interp.get_input_details()[0]["index"]
output_tensor = interp.get_output_details()[0]["index"]
interp.set_tensor(input_tensor, test_data)
interp.invoke()
out_tflite = interp.get_tensor(output_tensor)
out_tf = model_sd(input_points = test_data)["output"]
# Comparing the "out_tf" and "out_tflite" tensors, it can be observed that results will be off by a significant margin.
Issue Type
Bug
OS
Ubuntu
OS architecture
x86_64
Programming Language
Python
Framework
TensorFlow, TensorFlowLite
Model name and Weights/Checkpoints URL
390_BlendshapeV2
Description
TensorFlow Saved Model format version of the BlendshapeV2 model yields significantly different results from the TFLite Version (face_blendshapes.tflite)
Relevant Log Output
No response
URL or source code for simple inference testing code