def color_ratios(img):
check_img_arg(img)
n = np.prod(img.shape[:2])
imh = img_to_2d_num_hash(img)
counts = Counter(np.ravel(imh))
color_ratios = [float(count) / n for _, count in counts.items()]
return color_ratios
def save(img, savefile, use_default=False):
check_img_arg(img)
if use_default:
savefile = os.path.join(DEFAULT_DIR, savefile)
else:
savedir = os.path.dirname(savefile)
if not os.path.isdir(savedir):
print('WARNING: creating directory {}'.format(savedir))
os.mkdir(savedir)
mplim.imsave(savefile, img)
def save_as_gif(imgs, savefile, use_default=False):
if not isinstance(imgs, list):
raise TypeError('Expecting a list as first argument.')
check_img_arg(imgs[0], allow_grayscale=True)
if use_default:
savefile = os.path.join(DEFAULT_DIR, savefile)
else:
savedir = os.path.dirname(savefile)
if not os.path.isdir(savedir):
print('WARNING: creating directory {}'.format(savedir))
os.mkdir(savedir)
with imageio.get_writer(savefile, mode='I') as writer:
for img in imgs:
writer.append_data(img)
def display_info(imgfile, img=None):
check_imgfile_arg(imgfile)
# size of file, format, dimension
etype = imgfile.split('.')[-1].upper()
ftype = identify_format(imgfile)
fsize, size_descr = identify_filesize(imgfile)
if img is not None:
check_img_arg(img)
fdim = img.shape[:2]
else:
fdim = identify_dimensions(imgfile)
print('Extension : {}'.format(etype))
print('True format : {}'.format(ftype))
print('Dimensions : {} x {}'.format(*fdim))
print('Size of file : {} {}'.format(fsize, size_descr))
def background_color(img):
check_img_arg(img)
mode = Counter(np.ravel(img_to_2d_num_hash(img))).most_common(1)[0][0]
return np.array(num_hash_to_rgb(int(mode)))
def dist_to_color(img, col):
check_img_arg(img)
col = check_color(col, to_numpy=True)
return np.linalg.norm(img - col[np.newaxis, np.newaxis, :])
def glob_luminance(img):
check_img_arg(img)
return np.mean(img_to_luminance(img))
def num_colors(img):
check_img_arg(img)
return len(np.unique(np.ravel(img_to_2d_num_hash(img))))
def complement(img):
check_img_arg(img)
h, w = img.shape[:2]
img_mod = np.array(
[complementary_color(img[i, j]) for i in range(h) for j in range(w)])
return img_mod.reshape(img.shape)