Python OpenCV's style YAML dumpbased on: http://stackoverflow.com/questions/11141336/filestorage-for-opencv-python-api/15942429

opencv_yaml.py

# A yaml constructor is for loading from a yaml node.
# This is taken from @misha 's answer: http://stackoverflow.com/a/15942429
def opencv_matrix_constructor(loader, node):
    mapping = loader.construct_mapping(node, deep=True)
    mat = np.array(mapping["data"])
    mat.resize(mapping["rows"], mapping["cols"])
    return mat
yaml.add_constructor(u"tag:yaml.org,2002:opencv-matrix", opencv_matrix_constructor)

# A yaml representer is for dumping structs into a yaml node.
# So for an opencv_matrix type (to be compatible with c++'s FileStorage) we save the rows, cols, type and flattened-data
def opencv_matrix_representer(dumper, mat):
    if len(mat.shape)>1: cols=int(mat.shape[1])
    else: cols=1
    mapping = {'rows': int(mat.shape[0]), 'cols': cols, 'dt': 'd', 'data': mat.reshape(-1).tolist()}
    return dumper.represent_mapping(u"tag:yaml.org,2002:opencv-matrix", mapping)
yaml.add_representer(np.ndarray, opencv_matrix_representer)
yaml.add_representer(np.ndarray, opencv_matrix_representer)

def load_opencv_yaml(filename, skiplines=1):
    with open(filename, 'r') as f:
        for i in range(skiplines):
            _ = f.readline()
            data = yaml.load(f)
    return data

def write_opencv_yaml(data, filename):
    header = '%YAML:1.0\n'
    with open(filename, 'w') as f:
        f.write(header)
        yaml.dump(data, f)

if __name__ == "__main__":
    with open('output.yaml', 'w') as f:
        yaml.dump({"a_matrix": np.zeros((10,10)), "another_one": np.zeros((2,4))}, f)

    with open('output.yaml', 'r') as f:
        print(yaml.load(f)['a_matrix'])