f4334277
 Hu Chunming
提交3rdparty
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#include <opencv2/core/utils/filesystem.hpp>
using namespace cv;
std::string genArgument(const std::string& argName, const std::string& help,
const std::string& modelName, const std::string& zooFile,
char key = ' ', std::string defaultVal = "");
std::string genPreprocArguments(const std::string& modelName, const std::string& zooFile);
std::string findFile(const std::string& filename);
std::string genArgument(const std::string& argName, const std::string& help,
const std::string& modelName, const std::string& zooFile,
char key, std::string defaultVal)
{
if (!modelName.empty())
{
FileStorage fs(zooFile, FileStorage::READ);
if (fs.isOpened())
{
FileNode node = fs[modelName];
if (!node.empty())
{
FileNode value = node[argName];
if (!value.empty())
{
if (value.isReal())
defaultVal = format("%f", (float)value);
else if (value.isString())
defaultVal = (std::string)value;
else if (value.isInt())
defaultVal = format("%d", (int)value);
else if (value.isSeq())
{
for (size_t i = 0; i < value.size(); ++i)
{
FileNode v = value[(int)i];
if (v.isInt())
defaultVal += format("%d ", (int)v);
else if (v.isReal())
defaultVal += format("%f ", (float)v);
else
CV_Error(Error::StsNotImplemented, "Unexpected value format");
}
}
else
CV_Error(Error::StsNotImplemented, "Unexpected field format");
}
}
}
}
return "{ " + argName + " " + key + " | " + defaultVal + " | " + help + " }";
}
std::string findFile(const std::string& filename)
{
if (filename.empty() || utils::fs::exists(filename))
return filename;
const char* extraPaths[] = {getenv("OPENCV_DNN_TEST_DATA_PATH"),
getenv("OPENCV_TEST_DATA_PATH")};
for (int i = 0; i < 2; ++i)
{
if (extraPaths[i] == NULL)
continue;
std::string absPath = utils::fs::join(extraPaths[i], utils::fs::join("dnn", filename));
if (utils::fs::exists(absPath))
return absPath;
}
CV_Error(Error::StsObjectNotFound, "File " + filename + " not found! "
"Please specify a path to /opencv_extra/testdata in OPENCV_DNN_TEST_DATA_PATH "
"environment variable or pass a full path to model.");
}
std::string genPreprocArguments(const std::string& modelName, const std::string& zooFile)
{
return genArgument("model", "Path to a binary file of model contains trained weights. "
"It could be a file with extensions .caffemodel (Caffe), "
".pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet), .bin (OpenVINO).",
modelName, zooFile, 'm') +
genArgument("config", "Path to a text file of model contains network configuration. "
"It could be a file with extensions .prototxt (Caffe), .pbtxt (TensorFlow), .cfg (Darknet), .xml (OpenVINO).",
modelName, zooFile, 'c') +
genArgument("mean", "Preprocess input image by subtracting mean values. Mean values should be in BGR order and delimited by spaces.",
modelName, zooFile) +
genArgument("scale", "Preprocess input image by multiplying on a scale factor.",
modelName, zooFile, ' ', "1.0") +
genArgument("width", "Preprocess input image by resizing to a specific width.",
modelName, zooFile, ' ', "-1") +
genArgument("height", "Preprocess input image by resizing to a specific height.",
modelName, zooFile, ' ', "-1") +
genArgument("rgb", "Indicate that model works with RGB input images instead BGR ones.",
modelName, zooFile);
}
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