我正在尝试在opencv中提供以下gitrepo：https://github.com/una-dinosauria/3d-pose-baseline，检查点数据可以在以下链接找到：https://drive.google.com/file/d/0BxWzojlLp259MF9qSFpiVjl0cU0/view
我已经构建了一个冻结的图表，可以在python中使用，并使用以下脚本生成：
然后我通过运行以下命令来优化图形：
我附上了在OpenCV中导致该问题的函数：
meta_path = 'checkpoint-4874200.meta' # Your .meta file
output_node_names = ['linear_model/add_1'] # Output nodes
export_dir=os.path.join('export_dir')
graph=tf.Graph()
with tf.Session(graph=graph) as sess:
# Restore the graph
loader=tf.train.import_meta_graph(meta_path)
loader.restore(sess,'checkpoint-4874200')
builder=tf.saved_model.builder.SavedModelBuilder(export_dir)
builder.add_meta_graph_and_variables(sess,
[tf.saved_model.SERVING],
strip_default_attrs=True)
# Freeze the graph
frozen_graph_def = tf.graph_util.convert_variables_to_constants(
sess,
sess.graph_def,
output_node_names)
# Save the frozen graph
with open('C:\\Users\\FrozenGraph.pb', 'wb') as f:
f.write(frozen_graph_def.SerializeToString())
然后我通过运行以下命令来优化图形：
optimized_graph_def=optimize_for_inference_lib.optimize_for_inference(
frozen_graph_def,
['inputs/enc_in'],
['linear_model/add_1'],
tf.float32.as_datatype_enum)
g=tf.gfile.FastGFile('optimized_inference_graph.pb','wb')
g.write(optimized_graph_def.SerializeToString())
优化后的冻结图可以在以下链接中找到: https://github.com/alecda573/frozen_graph/blob/master/optimized_inference_graph.pb
当我尝试在OpenCV中运行以下内容时，会出现运行时错误:
OpenCV(4.3.0) Error: Unspecified error (More than one input is Const op) in cv::dnn::dnn4_v20200310::`anonymous-namespace'::TFImporter::getConstBlob, file C:\build\master_winpack-build-win64-vc15\opencv\modules\dnn\src\tensorflow\tf_importer.cpp, line 570
重现步骤
要重现问题，您只需要从上面的链接下载冻结图或从检查点数据创建自己的冻结图，然后使用下面的头文件在opencv中调用以下内容：
#include <iostream>
#include <vector>
#include <cmath>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include "opencv2/dnn.hpp"
string pbFilePath = "C:/Users/optimized_inferene_graph.pb";
//Create 3d-pose-baseline model
cv::dnn::Net inputNet;
inputNet = cv::dnn::readNetFromTensorflow(pbFilePath);
我希望知道是否有人对如何解决这个错误有任何想法。
您可以从附加的照片中看到我使用tensorboard生成的冻结图和优化图。
我附上了在OpenCV中导致该问题的函数：
const tensorflow::TensorProto& TFImporter::getConstBlob(const tensorflow::NodeDef &layer, std::map<String, int> const_layers,
int input_blob_index, int* actual_inp_blob_idx) {
if (input_blob_index == -1) {
for(int i = 0; i < layer.input_size(); i++) {
Pin input = parsePin(layer.input(i));
if (const_layers.find(input.name) != const_layers.end()) {
if (input_blob_index != -1)
CV_Error(Error::StsError, "More than one input is Const op");
input_blob_index = i;
}
}
}
if (input_blob_index == -1)
CV_Error(Error::StsError, "Const input blob for weights not found");
Pin kernel_inp = parsePin(layer.input(input_blob_index));
if (const_layers.find(kernel_inp.name) == const_layers.end())
CV_Error(Error::StsError, "Input [" + layer.input(input_blob_index) +
"] for node [" + layer.name() + "] not found");
if (kernel_inp.blobIndex != 0)
CV_Error(Error::StsError, "Unsupported kernel input");
if(actual_inp_blob_idx) {
*actual_inp_blob_idx = input_blob_index;
}
int nodeIdx = const_layers.at(kernel_inp.name);
if (nodeIdx < netBin.node_size() && netBin.node(nodeIdx).name() == kernel_inp.name)
{
return netBin.node(nodeIdx).attr().at("value").tensor();
}
else
{
CV_Assert_N(nodeIdx < netTxt.node_size(),
netTxt.node(nodeIdx).name() == kernel_inp.name);
return netTxt.node(nodeIdx).attr().at("value").tensor();
}
}