357 KiB
357 KiB
import tensorflow as tf
from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2model = tf.keras.models.load_model('./model')# Convert Keras model to ConcreteFunction
full_model = tf.function(lambda x: model(x))
full_model = full_model.get_concrete_function(
tf.TensorSpec(model.inputs[0].shape, model.inputs[0].dtype))
# Get frozen ConcreteFunction
frozen_func = convert_variables_to_constants_v2(full_model)
frozen_func.graph.as_graph_def()
# Save frozen graph from frozen ConcreteFunction to hard drive
tf.io.write_graph(graph_or_graph_def=frozen_func.graph,
logdir="./frozen_models",
name="frozen_graph.pb",
as_text=False)'./frozen_models\\\\frozen_graph.pb'
def wrap_frozen_graph(graph_def, inputs, outputs, print_graph=False):
def _imports_graph_def():
tf.compat.v1.import_graph_def(graph_def, name="")
wrapped_import = tf.compat.v1.wrap_function(_imports_graph_def, [])
import_graph = wrapped_import.graph
if print_graph == True:
print("-" * 50)
print("Frozen model layers: ")
layers = [op.name for op in import_graph.get_operations()]
for layer in layers:
print(layer)
print("-" * 50)
return wrapped_import.prune(
tf.nest.map_structure(import_graph.as_graph_element, inputs),
tf.nest.map_structure(import_graph.as_graph_element, outputs)) # Load frozen graph using TensorFlow 1.x functions
with tf.io.gfile.GFile("./frozen_models/frozen_graph_best.pb", "rb") as f:
graph_def = tf.compat.v1.GraphDef()
loaded = graph_def.ParseFromString(f.read())
# Wrap frozen graph to ConcreteFunctions
frozen_func = wrap_frozen_graph(graph_def=graph_def,
inputs=["x:0"],
outputs=["Identity:0"],
print_graph=True)-------------------------------------------------- Frozen model layers: x sequential/conv2d/Conv2D/ReadVariableOp/resource sequential/conv2d/Conv2D/ReadVariableOp sequential/conv2d/Conv2D sequential/conv2d/BiasAdd/ReadVariableOp/resource sequential/conv2d/BiasAdd/ReadVariableOp sequential/conv2d/BiasAdd sequential/conv2d/Relu sequential/batch_normalization/ReadVariableOp/resource sequential/batch_normalization/ReadVariableOp sequential/batch_normalization/ReadVariableOp_1/resource sequential/batch_normalization/ReadVariableOp_1 sequential/batch_normalization/FusedBatchNormV3/ReadVariableOp/resource sequential/batch_normalization/FusedBatchNormV3/ReadVariableOp sequential/batch_normalization/FusedBatchNormV3/ReadVariableOp_1/resource sequential/batch_normalization/FusedBatchNormV3/ReadVariableOp_1 sequential/batch_normalization/FusedBatchNormV3 sequential/max_pooling2d/MaxPool sequential/conv2d_1/Conv2D/ReadVariableOp/resource sequential/conv2d_1/Conv2D/ReadVariableOp sequential/conv2d_1/Conv2D sequential/conv2d_1/BiasAdd/ReadVariableOp/resource sequential/conv2d_1/BiasAdd/ReadVariableOp sequential/conv2d_1/BiasAdd sequential/conv2d_1/Relu sequential/batch_normalization_1/ReadVariableOp/resource sequential/batch_normalization_1/ReadVariableOp sequential/batch_normalization_1/ReadVariableOp_1/resource sequential/batch_normalization_1/ReadVariableOp_1 sequential/batch_normalization_1/FusedBatchNormV3/ReadVariableOp/resource sequential/batch_normalization_1/FusedBatchNormV3/ReadVariableOp sequential/batch_normalization_1/FusedBatchNormV3/ReadVariableOp_1/resource sequential/batch_normalization_1/FusedBatchNormV3/ReadVariableOp_1 sequential/batch_normalization_1/FusedBatchNormV3 sequential/max_pooling2d_1/MaxPool sequential/conv2d_2/Conv2D/ReadVariableOp/resource sequential/conv2d_2/Conv2D/ReadVariableOp sequential/conv2d_2/Conv2D sequential/conv2d_2/BiasAdd/ReadVariableOp/resource sequential/conv2d_2/BiasAdd/ReadVariableOp sequential/conv2d_2/BiasAdd sequential/conv2d_2/Relu sequential/batch_normalization_2/ReadVariableOp/resource sequential/batch_normalization_2/ReadVariableOp sequential/batch_normalization_2/ReadVariableOp_1/resource sequential/batch_normalization_2/ReadVariableOp_1 sequential/batch_normalization_2/FusedBatchNormV3/ReadVariableOp/resource sequential/batch_normalization_2/FusedBatchNormV3/ReadVariableOp sequential/batch_normalization_2/FusedBatchNormV3/ReadVariableOp_1/resource sequential/batch_normalization_2/FusedBatchNormV3/ReadVariableOp_1 sequential/batch_normalization_2/FusedBatchNormV3 sequential/conv2d_3/Conv2D/ReadVariableOp/resource sequential/conv2d_3/Conv2D/ReadVariableOp sequential/conv2d_3/Conv2D sequential/conv2d_3/BiasAdd/ReadVariableOp/resource sequential/conv2d_3/BiasAdd/ReadVariableOp sequential/conv2d_3/BiasAdd sequential/conv2d_3/Relu sequential/batch_normalization_3/ReadVariableOp/resource sequential/batch_normalization_3/ReadVariableOp sequential/batch_normalization_3/ReadVariableOp_1/resource sequential/batch_normalization_3/ReadVariableOp_1 sequential/batch_normalization_3/FusedBatchNormV3/ReadVariableOp/resource sequential/batch_normalization_3/FusedBatchNormV3/ReadVariableOp sequential/batch_normalization_3/FusedBatchNormV3/ReadVariableOp_1/resource sequential/batch_normalization_3/FusedBatchNormV3/ReadVariableOp_1 sequential/batch_normalization_3/FusedBatchNormV3 sequential/conv2d_4/Conv2D/ReadVariableOp/resource sequential/conv2d_4/Conv2D/ReadVariableOp sequential/conv2d_4/Conv2D sequential/conv2d_4/BiasAdd/ReadVariableOp/resource sequential/conv2d_4/BiasAdd/ReadVariableOp sequential/conv2d_4/BiasAdd sequential/conv2d_4/Relu sequential/batch_normalization_4/ReadVariableOp/resource sequential/batch_normalization_4/ReadVariableOp sequential/batch_normalization_4/ReadVariableOp_1/resource sequential/batch_normalization_4/ReadVariableOp_1 sequential/batch_normalization_4/FusedBatchNormV3/ReadVariableOp/resource sequential/batch_normalization_4/FusedBatchNormV3/ReadVariableOp sequential/batch_normalization_4/FusedBatchNormV3/ReadVariableOp_1/resource sequential/batch_normalization_4/FusedBatchNormV3/ReadVariableOp_1 sequential/batch_normalization_4/FusedBatchNormV3 sequential/max_pooling2d_2/MaxPool sequential/flatten/Const sequential/flatten/Reshape sequential/dense/MatMul/ReadVariableOp/resource sequential/dense/MatMul/ReadVariableOp sequential/dense/MatMul sequential/dense/BiasAdd/ReadVariableOp/resource sequential/dense/BiasAdd/ReadVariableOp sequential/dense/BiasAdd sequential/dense/Relu sequential/dense_1/MatMul/ReadVariableOp/resource sequential/dense_1/MatMul/ReadVariableOp sequential/dense_1/MatMul sequential/dense_1/BiasAdd/ReadVariableOp/resource sequential/dense_1/BiasAdd/ReadVariableOp sequential/dense_1/BiasAdd sequential/dense_1/Relu sequential/dense_2/MatMul/ReadVariableOp/resource sequential/dense_2/MatMul/ReadVariableOp sequential/dense_2/MatMul sequential/dense_2/BiasAdd/ReadVariableOp/resource sequential/dense_2/BiasAdd/ReadVariableOp sequential/dense_2/BiasAdd sequential/dense_2/Softmax NoOp Identity --------------------------------------------------
import cv2 as cvfish = cv.imread('./new_data/train/Jellyfish/03Q7BTGDW34G.jpg')fish = cv.resize(fish, (227, 227), interpolation=cv.INTER_AREA)class_names=sorted(['Fish', "Jellyfish", 'Penguin', 'Puffin', 'Shark', 'Starfish', 'Stingray'])frozen_func(x=tf.convert_to_tensor(fish[None, :], dtype="float32"))[0].numpy()array([[0., 0., 0., 0., 0., 0., 1., 0., 0., 0.]], dtype=float32)
import numpy as np
from PIL import Imagefishes = [
tf.convert_to_tensor(cv.resize(cv.imread('./new_data/train/Shark/D3U6ZGZZCQTF.jpg'), (227,227),interpolation=cv.INTER_AREA)[None, :], dtype='float32'),
tf.convert_to_tensor(cv.resize(cv.imread('./new_data/train/Shark/08XY6WGTVFYN.jpg'), (227,227), interpolation=cv.INTER_AREA)[None, :], dtype='float32')
]frozen_func(x=fishes[0])[<tf.Tensor: shape=(1, 10), dtype=float32, numpy=array([[1., 0., 0., 0., 0., 0., 0., 0., 0., 0.]], dtype=float32)>]
fish_path = './new_data/test/4R4JNOPP4WYE.jpg'
fish = cv.imread(fish_path)
fish = cv.resize(fish, (227, 227), interpolation=cv.INTER_AREA)
print(frozen_func(x=tf.convert_to_tensor(fish[None, :], dtype='float32')))
print(f"Category: {class_names[np.argmax(frozen_func(x=tf.convert_to_tensor(fish[None, :], dtype='float32'))[0].numpy())]}")
Image.open(fish_path)[<tf.Tensor: shape=(1, 6), dtype=float32, numpy=array([[1., 0., 0., 0., 0., 0.]], dtype=float32)>] Category: Fish