def pil_to_ascii(img,
scalefactor=0.2,
invert=False,
equalize=True,
lut='simple',
aspect_correction_factor=None
):
"""
Generates an ascii string from a PIL image.
Parameters
----------
img : PIL.Image
PIL image to transform.
scalefactor : float
ASCII characters per pixel.
invert : bool
Invert luminance?
equalize : bool
equalize histogram (for best results do this).
lut : str
Name of the lookup table to use. Currently supports 'simple' and
'binary'.
Returns
-------
str
Examples
--------
>>> from asciisciit.misc import open_pil_img
>>> img = open_pil_img("http://i.imgur.com/l2FU2J0.jpg")
>>> text_img = pil_to_ascii(img, scalefactor=0.3)
>>> print(text_img)
>>> from PIL import Image
>>> img = Image.open("some_image.png")
>>> text_img = pil_to_ascii(img)
>>> print(text_img)
"""
lookup = get_lut(lut)
if aspect_correction_factor is None:
aspect_correction_factor = get_aspect_correction_factor(lookup.exemplar)
img = img.resize(
(int(img.size[0]*scalefactor),
int(img.size[1]*scalefactor*aspect_correction_factor)),
Image.BILINEAR)
img = img.convert("L") # convert to mono
if equalize:
img = ImageOps.equalize(img)
if invert:
img = ImageOps.invert(img)
img = np.array(img, dtype=np.uint8)
return u"\n" + u"".join(lookup.apply(img).flatten().tolist())
def pil_to_ascii(img,
scalefactor=0.2,
invert=False,
equalize=True,
lut='simple',
aspect_correction_factor=None):
"""
Generates an ascii string from a PIL image.
Parameters
----------
img : PIL.Image
PIL image to transform.
scalefactor : float
ASCII characters per pixel.
invert : bool
Invert luminance?
equalize : bool
equalize histogram (for best results do this).
lut : str
Name of the lookup table to use. Currently supports 'simple' and
'binary'.
Returns
-------
str
Examples
--------
>>> from asciisciit.misc import open_pil_img
>>> img = open_pil_img("http://i.imgur.com/l2FU2J0.jpg")
>>> text_img = pil_to_ascii(img, scalefactor=0.3)
>>> print(text_img)
>>> from PIL import Image
>>> img = Image.open("some_image.png")
>>> text_img = pil_to_ascii(img)
>>> print(text_img)
"""
lookup = get_lut(lut)
if aspect_correction_factor is None:
aspect_correction_factor = get_aspect_correction_factor(
lookup.exemplar)
img = img.resize(
(int(img.size[0] * scalefactor),
int(img.size[1] * scalefactor * aspect_correction_factor)),
Image.BILINEAR)
img = img.convert("L") # convert to mono
if equalize:
img = ImageOps.equalize(img)
if invert:
img = ImageOps.invert(img)
img = np.array(img, dtype=np.uint8)
return u"\n" + u"".join(lookup.apply(img).flatten().tolist())
def numpy_to_ascii(img,
scalefactor=0.2,
invert=False,
equalize=True,
lut="simple",
aspect_correction_factor=None):
"""
Generates an ascii string from a numpy image.
Parameters
----------
img : ndarray
PIL image to transform.
scalefactor : float
ASCII characters per pixel.
invert : bool
Invert luminance?
equalize : bool
equalize histogram (for best results do this).
lut : str
Name of the lookup table to use. Currently supports 'simple' and
'binary'.
Returns
-------
str
"""
lookup = get_lut(lut)
if aspect_correction_factor is None:
aspect_correction_factor = get_aspect_correction_factor(lookup.exemplar)
h, w = img.shape
img = cv2.resize(
img,
(
int(w*scalefactor),
int(h*scalefactor*aspect_correction_factor)
)
)
if img.ndim == 3: # weak check for RGB
# works in opencv 3.4.3 but who knows, they keep moving/renaming stuff
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
if equalize:
img=cv2.equalizeHist(img)
if invert:
img = 255-img
return u"\n" + u"".join(lookup.apply(img).flatten().tolist())
def numpy_to_ascii(img,
scalefactor=0.2,
invert=False,
equalize=True,
lut="simple",
aspect_correction_factor=None):
"""
Generates an ascii string from a numpy image.
Parameters
----------
img : ndarray
PIL image to transform.
scalefactor : float
ASCII characters per pixel.
invert : bool
Invert luminance?
equalize : bool
equalize histogram (for best results do this).
lut : str
Name of the lookup table to use. Currently supports 'simple' and
'binary'.
Returns
-------
str
"""
lookup = get_lut(lut)
if aspect_correction_factor is None:
aspect_correction_factor = get_aspect_correction_factor(
lookup.exemplar)
h, w = img.shape
img = cv2.resize(img, (int(
w * scalefactor), int(h * scalefactor * aspect_correction_factor)))
if img.ndim == 3: # weak check for RGB
# works in opencv 3.4.3 but who knows, they keep moving/renaming stuff
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
if equalize:
img = cv2.equalizeHist(img)
if invert:
img = 255 - img
return u"\n" + u"".join(lookup.apply(img).flatten().tolist())
def lut(self, val):
self._lut = val
lookup = get_lut(val)
self.aspect_correction_factor = get_aspect_correction_factor(
lookup.exemplar, self.font_path) # default correction factor for converting
def lut(self, val):
self._lut = val
lookup = get_lut(val)
self.aspect_correction_factor = get_aspect_correction_factor(
lookup.exemplar, self.font_path) # default correction factor for converting
def test_get_lut():
assert(u"\u3105\u3106\u3107\u3108" not in lut.UNICODE_LUTS)
l1 = lut.get_lut("\u3105\u3106\u3107\u3108")
assert(u"\u3105\u3106\u3107\u3108" in lut.UNICODE_LUTS)
l2 = lut.get_lut("\u3105\u3106\u3107\u3108")