SPPAS 4.20

Module sppas.src.imgdata

Class NeuralNetCaffeDetector

Description

Detect objects in an image with an Artificial Neural Network.

Constructor

View Source 
def __init__(self):
    super(NeuralNetCaffeDetector, self).__init__()
    self._extension = '.caffemodel'

Private functions

_set_detector

Initialize the model with the given file.

Parameters
  • model: (str) Filename of the Caffe model file
Raises

IOError, Exception

View Source 
def _set_detector(self, model):
    """Initialize the model with the given file.

        :param model: (str) Filename of the Caffe model file
        :raise: IOError, Exception

        """
    fn, fe = os.path.splitext(model)
    proto = fn + '.prototxt'
    if os.path.exists(proto) is False:
        raise sppasIOError(proto)
    try:
        self._detector = cv2.dnn.readNetFromCaffe(proto, model)
    except cv2.error as e:
        logging.error('Artificial Neural Network model or proto (Caffe) failed to be read.')
        raise sppasError(str(e))
_net_detections

Initialize net and blob for the processing.

Returns
  • detections.
Parameters
  • image
View Source 
def _net_detections(self, image):
    """Initialize net and blob for the processing.

        :returns: detections.

        """
    img = image.iresize(width=0, height=360)
    w, h = img.size()
    blob = cv2.dnn.blobFromImage(img, 1.0, (w, h), (103.93, 116.77, 123.68))
    self._detector.setInput(blob)
    return self._detector.forward()