Python cv2.createLineSegmentDetector() Examples

The following are 4 code examples of cv2.createLineSegmentDetector(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module cv2 , or try the search function .
Example #1
Source File: pano_lsd_align.py    From pytorch-layoutnet with MIT License 5 votes vote down vote up 
def lsdWrap(img, LSD=None, **kwargs):
    '''
    Opencv implementation of
    Rafael Grompone von Gioi, Jérémie Jakubowicz, Jean-Michel Morel, and Gregory Randall,
    LSD: a Line Segment Detector, Image Processing On Line, vol. 2012.
    [Rafael12] http://www.ipol.im/pub/art/2012/gjmr-lsd/?utm_source=doi
    @img
        input image
    @LSD
        Constructing by cv2.createLineSegmentDetector
        https://docs.opencv.org/3.0-beta/modules/imgproc/doc/feature_detection.html#linesegmentdetector
        if LSD is given, kwargs will be ignored
    @kwargs
        is used to construct LSD
        work only if @LSD is not given
    '''
    if LSD is None:
        LSD = cv2.createLineSegmentDetector(**kwargs)

    if len(img.shape) == 3:
        img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

    lines, width, prec, nfa = LSD.detect(img)
    if lines is None:
        return np.zeros_like(img), np.array([])
    edgeMap = LSD.drawSegments(np.zeros_like(img), lines)[..., -1]
    lines = np.squeeze(lines, 1)
    edgeList = np.concatenate([lines, width, prec, nfa], 1)
    return edgeMap, edgeList
Example #2
Source File: image.py    From soccerontable with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def robust_edge_detection(img):
    # Find edges
    kernel_size = 5
    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    blur_gray = cv2.GaussianBlur(gray, (kernel_size, kernel_size), 0)
    # io.imagesc(blur_gray)
    edges = cv2.Canny((blur_gray * 255).astype(np.uint8), 10, 200, apertureSize=5)
    # io.imagesc(edges)
    lsd = cv2.createLineSegmentDetector(0)
    lines = lsd.detect(edges)[0]  # Position 0 of the returned tuple are the detected lines

    long_lines = []
    for j in range(lines.shape[0]):
        x1, y1, x2, y2 = lines[j, 0, :]
        if np.linalg.norm(np.array([x1, y1]) - np.array([x2, y2])) > 50:
            long_lines.append(lines[j, :, :])

    lines = np.array(long_lines)
    edges = 1 * np.ones_like(img)
    drawn_img = lsd.drawSegments(edges, lines)
    edges = (drawn_img[:, :, 2] > 1).astype(np.float32)

    kernel = np.ones((7, 7), np.uint8)

    edges = cv2.morphologyEx(edges, cv2.MORPH_CLOSE, kernel)
    kernel = np.ones((3, 3), np.uint8)
    edges = cv2.morphologyEx(edges, cv2.MORPH_OPEN, kernel)

    return edges
Example #3
Source File: vp_detection.py    From XiaohuLuVPDetection with MIT License 5 votes vote down vote up 
def __detect_lines(self, img):
        """
        Detects lines using OpenCV LSD Detector
        """
        # Convert to grayscale if required
        if len(img.shape) == 3:
            img_copy = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        else:
            img_copy = img

        # Create LSD detector with default parameters
        lsd = cv2.createLineSegmentDetector(0)

        # Detect lines in the image
        # Returns a NumPy array of type N x 1 x 4 of float32
        # such that the 4 numbers in the last dimension are (x1, y1, x2, y2)
        # These denote the start and end positions of a line
        lines = lsd.detect(img_copy)[0]

        # Remove singleton dimension
        lines = lines[:, 0]

        # Filter out the lines whose length is lower than the threshold
        dx = lines[:, 2] - lines[:, 0]
        dy = lines[:, 3] - lines[:, 1]
        lengths = np.sqrt(dx * dx + dy * dy)
        mask = lengths >= self._length_thresh
        lines = lines[mask]

        # Store the lines internally
        self.__lines = lines

        # Return the lines
        return lines
Example #4
Source File: pano_lsd_align.py    From HorizonNet with MIT License 4 votes vote down vote up 
def lsdWrap(img, LSD=None, **kwargs):
    '''
    Opencv implementation of
    Rafael Grompone von Gioi, Jérémie Jakubowicz, Jean-Michel Morel, and Gregory Randall,
    LSD: a Line Segment Detector, Image Processing On Line, vol. 2012.
    [Rafael12] http://www.ipol.im/pub/art/2012/gjmr-lsd/?utm_source=doi
    @img
        input image
    @LSD
        Constructing by cv2.createLineSegmentDetector
        https://docs.opencv.org/3.0-beta/modules/imgproc/doc/feature_detection.html#linesegmentdetector
        if LSD is given, kwargs will be ignored
    @kwargs
        is used to construct LSD
        work only if @LSD is not given
    '''
    if LSD is None:
        LSD = cv2.createLineSegmentDetector(**kwargs)

    if len(img.shape) == 3:
        img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

    lines, width, prec, nfa = LSD.detect(img)
    if lines is None:
        return np.zeros_like(img), np.array([])
    edgeMap = LSD.drawSegments(np.zeros_like(img), lines)[..., -1]
    lines = np.squeeze(lines, 1)
    edgeList = np.concatenate([lines, width, prec, nfa], 1)
    return edgeMap, edgeList