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