def test_sepia_greater_than_1(): im = util.fill((4, 4), [174, 56, 3]) sepiaed_im = css.sepia(im, 2) sepiaed_im2 = css.sepia(im, 1) assert list(sepiaed_im.getdata()) == list(sepiaed_im2.getdata()) assert sepiaed_im.size == im.size assert sepiaed_im.mode == im.mode
def test_sepia_hsv(): im = util.fill((4, 4), [174, 56, 3]) im2 = im.convert('HSV') sepiaed_im = css.sepia(im) sepiaed_im2 = css.sepia(im2) sepiaed_im2_rgb = sepiaed_im2.convert('RGB') assert list(sepiaed_im.getdata()) == list(sepiaed_im2_rgb.getdata()) assert sepiaed_im2.size == im2.size assert sepiaed_im2.mode == im2.mode
def nashville(im): """Applies Nashville filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs1 = util.fill(cb.size, [247, 176, 153]) cm1 = ImageChops.darker(cb, cs1) cm1 = Image.blend(cb, cm1, .56) cs2 = util.fill(cb.size, [0, 70, 150]) cm2 = ImageChops.lighter(cm1, cs2) cr = Image.blend(cm1, cm2, .4) cr = css.sepia(cr, .2) cr = css.contrast(cr, 1.2) cr = css.brightness(cr, 1.05) cr = css.saturate(cr, 1.2) return cr
def test_sepia_0(): im = util.fill((4, 4), [174, 56, 3]) sepiaed_im = css.sepia(im, 0) assert list(sepiaed_im.getdata()) == list(im.getdata()) assert sepiaed_im.size == im.size assert sepiaed_im.mode == im.mode
def rise(im): """Applies Rise filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs1 = util.fill(cb.size, [236, 205, 169, .15]) cm1 = css.blending.multiply(cb, cs1) cs2 = util.fill(cb.size, [50, 30, 7, .4]) cm2 = css.blending.multiply(cb, cs2) gradient_mask1 = util.radial_gradient_mask(cb.size, length=.55) cm = Image.composite(cm1, cm2, gradient_mask1) cs3 = util.fill(cb.size, [232, 197, 152, .8]) cm3 = css.blending.overlay(cm, cs3) gradient_mask2 = util.radial_gradient_mask(cb.size, scale=.9) cm_ = Image.composite(cm3, cm, gradient_mask2) cr = Image.blend(cm, cm_, .6) # opacity cr = css.brightness(cr, 1.05) cr = css.sepia(cr, .2) cr = css.contrast(cr, .9) cr = css.saturate(cr, .9) return cr
def xpro2(im): """Applies X-pro II filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs1 = util.fill(cb.size, [230, 231, 224]) cs2 = util.fill(cb.size, [43, 42, 161]) cs2 = Image.blend(cb, cs2, .6) gradient_mask = util.radial_gradient_mask(cb.size, length=.4, scale=1.1) cs = Image.composite(cs1, cs2, gradient_mask) # TODO: improve alpha blending cm1 = css.blending.color_burn(cb, cs) cm2 = cm1.copy() cm2 = Image.blend(cb, cm2, .6) cr = Image.composite(cm1, cm2, gradient_mask) cr = css.sepia(cr, .3) return cr
def inkwell(im): """Applies Inkwell filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cr = css.sepia(cb, .3) cr = css.contrast(cr, 1.1) cr = css.brightness(cr, 1.1) cr = css.grayscale(cr) return cr
def brannan(im): """Applies Brannan filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs = util.fill(cb.size, [161, 44, 199, .31]) cr = css.blending.lighten(cb, cs) cr = css.sepia(cr, .5) cr = css.contrast(cr, 1.4) return cr
def earlybird(im): """Applies Earlybird filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs = util.radial_gradient(cb.size, [(208, 186, 142), (54, 3, 9), (29, 2, 16)], [.2, .85, 1]) cr = css.blending.overlay(cb, cs) cr = css.contrast(cr, .9) cr = css.sepia(cr, .2) return cr
def maven(im): """Applies Maven filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs = util.fill(cb.size, [3, 230, 26, .2]) cr = css.blending.hue(cb, cs) cr = css.sepia(cr, .25) cr = css.brightness(cr, .95) cr = css.contrast(cr, .95) cr = css.saturate(cr, 1.5) return cr
def valencia(im): """Applies Valencia filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs = util.fill(cb.size, [58, 3, 57]) cs = css.blending.exclusion(cb, cs) cr = Image.blend(cb, cs, .5) cr = css.contrast(cr, 1.08) cr = css.brightness(cr, 1.08) cr = css.sepia(cr, .08) return cr
def reyes(im): """Applies Reyes filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs = util.fill(cb.size, [239, 205, 173]) cs = css.blending.soft_light(cb, cs) cr = Image.blend(cb, cs, .5) cr = css.sepia(cr, .22) cr = css.brightness(cr, 1.1) cr = css.contrast(cr, .85) cr = css.saturate(cr, .75) return cr
def walden(im): """Applies Walden filter. Arguments: im: An input image. Returns: The output image. """ cb = util.or_convert(im, 'RGB') cs = util.fill(cb.size, [0, 68, 204]) cs = ImageChops.screen(cb, cs) cr = Image.blend(cb, cs, .3) cr = css.brightness(cr, 1.1) cr = css.hue_rotate(cr, -10) cr = css.sepia(cr, .3) cr = css.saturate(cr, 1.6) return cr
def test_sepia_less_than_0(): with pytest.raises(AssertionError): im = util.fill((4, 4), [174, 56, 3]) css.sepia(im, -1)
def test_sepia(): im = util.fill((4, 4), [174, 56, 3]) sepiaed_im = css.sepia(im) assert sepiaed_im.size == im.size assert sepiaed_im.mode == im.mode