Python skimage.color.rgb2ycbcr() Examples

The following are 14 code examples of skimage.color.rgb2ycbcr(). 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 skimage.color , or try the search function .
Example #1
Source File: common.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)

        return img

    return [_set_channel(a) for a in args]
Example #2
Source File: common.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)

        return img

    return [_set_channel(a) for a in args]
Example #3
Source File: common.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)

        return img

    return [_set_channel(a) for a in args]
Example #4
Source File: common.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)

        return img

    return [_set_channel(a) for a in args]
Example #5
Source File: common.py    From OISR-PyTorch with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)

        return img

    return [_set_channel(a) for a in args]
Example #6
Source File: common.py    From EDSR-PyTorch with MIT License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)

        return img

    return [_set_channel(a) for a in args]
Example #7
Source File: common.py    From 3D_Appearance_SR with MIT License 5 votes vote down vote up 
def set_channel(l, n_channel):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channel == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channel == 3 and c == 1:
            img = np.concatenate([img] * n_channel, 2)

        return img

    return [_set_channel(_l) for _l in l]
Example #8
Source File: common.py    From AWSRN with MIT License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)
        return img

    return [_set_channel(a) for a in args]
Example #9
Source File: common.py    From NTIRE2019_EDRN with MIT License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)

        return img

    return [_set_channel(a) for a in args]
Example #10
Source File: common.py    From 2018_subeesh_epsr_eccvw with MIT License 5 votes vote down vote up 
def set_channel(l, n_channel):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channel == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channel == 3 and c == 1:
            img = np.concatenate([img] * n_channel, 2)

        return img

    return [_set_channel(_l) for _l in l]
Example #11
Source File: benchmark.py    From tensorflow-SRGAN with MIT License 5 votes vote down vote up 
def luminance(self, image):
    # Get luminance
    lum = rgb2ycbcr(image)[:,:,0]
    # Crop off 4 border pixels
    lum = lum[4:lum.shape[0]-4, 4:lum.shape[1]-4]
    #lum = lum.astype(np.float64)
    return lum
Example #12
Source File: common.py    From MSRN-PyTorch with MIT License 5 votes vote down vote up 
def set_channel(l, n_channel):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channel == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channel == 3 and c == 1:
            img = np.concatenate([img] * n_channel, 2)

        return img

    return [_set_channel(_l) for _l in l]
Example #13
Source File: common.py    From MSRN-PyTorch with MIT License 5 votes vote down vote up 
def set_channel(*args, n_channels=3):
    def _set_channel(img):
        if img.ndim == 2:
            img = np.expand_dims(img, axis=2)

        c = img.shape[2]
        if n_channels == 1 and c == 3:
            img = np.expand_dims(sc.rgb2ycbcr(img)[:, :, 0], 2)
        elif n_channels == 3 and c == 1:
            img = np.concatenate([img] * n_channels, 2)

        return img

    return [_set_channel(a) for a in args]
Example #14
Source File: metrics.py    From proSR with GNU General Public License v3.0 5 votes vote down vote up 
def eval_psnr_and_ssim(im1, im2, scale):
    im1_t = np.atleast_3d(img_as_float(im1))
    im2_t = np.atleast_3d(img_as_float(im2))

    if im1_t.shape[2] == 1 or im2_t.shape[2] == 1:
        im1_t = im1_t[..., 0]
        im2_t = im2_t[..., 0]

    else:
        im1_t = rgb2ycbcr(im1_t)[:, :, 0:1] / 255.0
        im2_t = rgb2ycbcr(im2_t)[:, :, 0:1] / 255.0

    if scale > 1:
        im1_t = mod_crop(im1_t, scale)
        im2_t = mod_crop(im2_t, scale)

        # NOTE conventionally, crop scale+6 pixels (EDSR, VDSR etc)
        im1_t = crop_boundaries(im1_t, int(scale) + 6)
        im2_t = crop_boundaries(im2_t, int(scale) + 6)

    psnr_val = compare_psnr(im1_t, im2_t)
    ssim_val = compare_ssim(
        im1_t,
        im2_t,
        win_size=11,
        gaussian_weights=True,
        multichannel=True,
        data_range=1.0,
        K1=0.01,
        K2=0.03,
        sigma=1.5)

    return psnr_val, ssim_val