Пример #1
0
bool operator==(const ::google::protobuf::RepeatedField<T>& a, const ::google::protobuf::RepeatedField<T>& b) {
	if (a.size() != b.size())
		return false;
	for (auto aiter=a.begin(), biter=b.begin(); aiter != a.end(); aiter++, biter++ ) {
		if (*aiter != *biter)
			return false;
	}

	return true;
}
Пример #2
0
Mat getMatFromTensor(opencv_onnx::TensorProto& tensor_proto)
{
    CV_Assert(!tensor_proto.raw_data().empty() || !tensor_proto.float_data().empty()
                    || !tensor_proto.double_data().empty() || !tensor_proto.int64_data().empty());

    opencv_onnx::TensorProto_DataType datatype = tensor_proto.data_type();
    Mat blob;
    std::vector<int> sizes;
    for (int i = 0; i < tensor_proto.dims_size(); i++) {
            sizes.push_back(tensor_proto.dims(i));
    }
    if (sizes.empty())
        sizes.assign(1, 1);
    if (datatype == opencv_onnx::TensorProto_DataType_FLOAT) {

        if (!tensor_proto.float_data().empty()) {
            const ::google::protobuf::RepeatedField<float> field = tensor_proto.float_data();
            Mat(sizes, CV_32FC1, (void*)field.data()).copyTo(blob);
        }
        else {
            char* val = const_cast<char*>(tensor_proto.raw_data().c_str());
            Mat(sizes, CV_32FC1, val).copyTo(blob);
        }
    }
    else if (datatype == opencv_onnx::TensorProto_DataType_DOUBLE)
    {
        const ::google::protobuf::RepeatedField<double> field = tensor_proto.double_data();
        CV_Assert(!field.empty());
        Mat(sizes, CV_64FC1, (void*)field.data()).convertTo(blob, CV_32FC1);
    }
    else if (datatype == opencv_onnx::TensorProto_DataType_INT64)
    {
        blob.create(sizes, CV_32SC1);
        int32_t* dst = reinterpret_cast<int32_t*>(blob.data);

        if (!tensor_proto.int64_data().empty()) {
            ::google::protobuf::RepeatedField< ::google::protobuf::int64> src = tensor_proto.int64_data();
            convertInt64ToInt32(src, dst, blob.total());
        }
        else
        {
            char* val = const_cast<char*>(tensor_proto.raw_data().c_str());
            int64_t* src = reinterpret_cast<int64_t*>(val);
            convertInt64ToInt32(src, dst, blob.total());
        }
    }
    else
        CV_Error(Error::StsUnsupportedFormat, "Unsupported data type: " +
                        opencv_onnx::TensorProto_DataType_Name(datatype));
    if (tensor_proto.dims_size() == 0)
        blob.dims = 1;  // To force 1-dimensional cv::Mat for scalars.
    return blob;
}
Пример #3
0
inline bool operator== (
        const google::protobuf::RepeatedField<T> & x,
        const google::protobuf::RepeatedField<T> & y)
{
    if (LOOM_UNLIKELY(x.size() != y.size())) {
        return false;
    }
    for (size_t i = 0, size = x.size(); i < size; ++i) {
        if (LOOM_UNLIKELY(x.Get(i) != y.Get(i))) {
            return false;
        }
    }
    return true;
}
Пример #4
0
	// Get an OSM tag for a given key (or return empty string if none)
	// Called from Lua
	string Find(const string& key) const {
		// First, convert the string into a number
		if (tagMap.find(key) == tagMap.end()) { return ""; }
		uint keyNum = tagMap.at(key);
		if (isWay) {
			// Then see if this number is in the way tags, and return its value if so
			for (uint n=0; n < tagLength; n++) {
				if (keysPtr->Get(n)==keyNum) { return stringTable[valsPtr->Get(n)]; }
			}
		} else {
			for (uint n=denseStart; n<denseEnd; n+=2) {
				if (densePtr->keys_vals(n)==keyNum) { return stringTable[densePtr->keys_vals(n+1)]; }
			}
		}
		return "";
	}
Пример #5
0
	// Check if there's a value for a given key
	// Called from Lua
	bool Holds(const string& key) const {
		if (tagMap.find(key) == tagMap.end()) { return false; }
		uint keyNum = tagMap.at(key);
		if (isWay) {
			for (uint n=0; n > tagLength; n++) {
				if (keysPtr->Get(n)==keyNum) { return true; }
			}
		} else {
			for (uint n=denseStart; n<denseEnd; n+=2) {
				if (densePtr->keys_vals(n)==keyNum) { return true; }
			}
		}
		return false;
	}