Python cv2.BORDER_WRAP Examples

The following are 6 code examples of cv2.BORDER_WRAP(). 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: visualize_mesh.py    From Structured3D with MIT License 6 votes vote down vote up 
def E2P(image, corner_i, corner_j, wall_height, camera, resolution=512, is_wall=True):
    """convert panorama to persepctive image
    """
    corner_i = corner_i - camera
    corner_j = corner_j - camera

    if is_wall:
        xs = np.linspace(corner_i[0], corner_j[0], resolution)[None].repeat(resolution, 0)
        ys = np.linspace(corner_i[1], corner_j[1], resolution)[None].repeat(resolution, 0)
        zs = np.linspace(-camera[-1], wall_height - camera[-1], resolution)[:, None].repeat(resolution, 1)
    else:
        xs = np.linspace(corner_i[0], corner_j[0], resolution)[None].repeat(resolution, 0)
        ys = np.linspace(corner_i[1], corner_j[1], resolution)[:, None].repeat(resolution, 1)
        zs = np.zeros_like(xs) + wall_height - camera[-1]

    coorx, coory = xyz_2_coorxy(xs, ys, zs)

    persp = cv2.remap(image, coorx.astype(np.float32), coory.astype(np.float32), 
                      cv2.INTER_CUBIC, borderMode=cv2.BORDER_WRAP)

    return persp
Example #2
Source File: deconvolution.py    From OpenCV-Python-Tutorial with MIT License 5 votes vote down vote up 
def blur_edge(img, d=31):
    h, w  = img.shape[:2]
    img_pad = cv2.copyMakeBorder(img, d, d, d, d, cv2.BORDER_WRAP)
    img_blur = cv2.GaussianBlur(img_pad, (2*d+1, 2*d+1), -1)[d:-d,d:-d]
    y, x = np.indices((h, w))
    dist = np.dstack([x, w-x-1, y, h-y-1]).min(-1)
    w = np.minimum(np.float32(dist)/d, 1.0)
    return img*w + img_blur*(1-w)
Example #3
Source File: blend.py    From imgaug with MIT License 5 votes vote down vote up 
def _smoothen_alphas(cls, alphas, sigma):
        if sigma <= 0.0+1e-2:
            return alphas

        ksize = max(int(sigma * 2.5), 3)
        ksize_y, ksize_x = (1, ksize)
        if ksize_x % 2 == 0:
            ksize_x += 1

        # we fake here cv2.BORDER_WRAP, because GaussianBlur does not
        # support that mode, i.e. we want:
        #   cdefgh|abcdefgh|abcdefg
        alphas = np.concatenate([
            alphas[-ksize_x:],
            alphas,
            alphas[:ksize_x],
        ])

        alphas = cv2.GaussianBlur(
            _normalize_cv2_input_arr_(alphas[np.newaxis, :]),
            ksize=(ksize_x, ksize_y),
            sigmaX=sigma, sigmaY=sigma,
            borderType=cv2.BORDER_REPLICATE
        )[0, :]

        # revert fake BORDER_WRAP
        alphas = alphas[ksize_x:-ksize_x]

        return alphas

    # Added in 0.4.0.
Example #4
Source File: deconvolution.py    From PyCV-time with MIT License 5 votes vote down vote up 
def blur_edge(img, d=31):
    h, w  = img.shape[:2]
    img_pad = cv2.copyMakeBorder(img, d, d, d, d, cv2.BORDER_WRAP)
    img_blur = cv2.GaussianBlur(img_pad, (2*d+1, 2*d+1), -1)[d:-d,d:-d]
    y, x = np.indices((h, w))
    dist = np.dstack([x, w-x-1, y, h-y-1]).min(-1)
    w = np.minimum(np.float32(dist)/d, 1.0)
    return img*w + img_blur*(1-w)
Example #5
Source File: deconvolution.py    From PyCV-time with MIT License 5 votes vote down vote up 
def blur_edge(img, d=31):
    h, w  = img.shape[:2]
    img_pad = cv2.copyMakeBorder(img, d, d, d, d, cv2.BORDER_WRAP)
    img_blur = cv2.GaussianBlur(img_pad, (2*d+1, 2*d+1), -1)[d:-d,d:-d]
    y, x = np.indices((h, w))
    dist = np.dstack([x, w-x-1, y, h-y-1]).min(-1)
    w = np.minimum(np.float32(dist)/d, 1.0)
    return img*w + img_blur*(1-w)
Example #6
Source File: augmenters.py    From netharn with Apache License 2.0 5 votes vote down vote up 
def __init__(self, target_size, fill_color=127, mode='letterbox',
                 border='constant', random_state=None):
        super(Resize, self).__init__(random_state=random_state)
        self.target_size = None if target_size is None else np.array(target_size)
        self.mode = mode

        import imgaug.parameters as iap
        if fill_color == imgaug.ALL:
            self.fill_color = iap.Uniform(0, 255)
        else:
            self.fill_color = iap.handle_continuous_param(
                fill_color, "fill_color", value_range=None,
                tuple_to_uniform=True, list_to_choice=True)

        self._cv2_border_type_map = {
            'constant': cv2.BORDER_CONSTANT,
            'edge': cv2.BORDER_REPLICATE,
            'linear_ramp': None,
            'maximum': None,
            'mean': None,
            'median': None,
            'minimum': None,
            'reflect': cv2.BORDER_REFLECT_101,
            'symmetric': cv2.BORDER_REFLECT,
            'wrap': cv2.BORDER_WRAP,
            cv2.BORDER_CONSTANT: cv2.BORDER_CONSTANT,
            cv2.BORDER_REPLICATE: cv2.BORDER_REPLICATE,
            cv2.BORDER_REFLECT_101: cv2.BORDER_REFLECT_101,
            cv2.BORDER_REFLECT: cv2.BORDER_REFLECT
        }
        if isinstance(border, six.string_types):
            if border == imgaug.ALL:
                border = [k for k, v in self._cv2_border_type_map.items()
                          if v is not None and isinstance(k, six.string_types)]
            else:
                border = [border]
        if isinstance(border, (list, tuple)):
            from imgaug.parameters import Choice
            border = Choice(border)
        self.border = border
        assert self.mode == 'letterbox', 'thats all folks'