# print("Image type %r recognized." % img.mode)
elif img.mode in 'LP':
print("Errored on", name)
print(("Image type %r recognized, but this program is not written" +
"for an 8-bit image.") % img.mode)
print("Unsure how to proceed; exiting.")
exit(1)
else:
print("Errored on", name)
print("Image type %r recognized, but not a 0-255 grayscale image." %
img.mode)
print("Unsure how to proceed; exiting.")
exit(4)
if args.limits is None:
inputs.append(list(image_iter(img)))
else:
inputs.append([im.crop(args.limits) for im in image_iter(img)])
def renorm_bin(arr, thresh, upper):
float_arr = np.asarray(arr, dtype=np.float)
normed = float_arr / upper_thresh
np.clip(normed, 0, 1, out=normed)
binned = arr > thresh
return normed, binned
def arr_to_img(arr):
return Image.fromarray(np.uint8(arr * 255))
try:
img = Image.open(str(args.input))
except FileNotFoundError as e:
print(e)
exit(2)
except OSError as e:
print(e)
exit(3)
if img.mode not in 'LP':
print("Image type %s recognized, but not a 0-255 grayscale image." %
img.mode)
print("Unsure how to proceed; exiting.")
exit(1)
img_list = (list(image_iter(img)) if args.limits is None else
[im.crop(args.limits) for im in image_iter(img)])
cyans_unnormalized = img_list[::2]
yellows_unnormalized = img_list[1::2]
hists = cyan_hist, yellow_hist = [
np.sum([im.histogram() for im in img_list], axis=0)
for img_list in (cyans_unnormalized, yellows_unnormalized)
]
def to_arr_lists(img_list, thresh, upper_thresh):
thresh, upper_thresh, lst, bin_lst = renormalize_all(
img_list, thresh, upper_thresh)
arrs = np.asarray([np.asarray(im) for im in lst], dtype=float) / MAX_PIXEL
bins = np.asarray([np.asarray(im) > 0 for im in bin_lst], dtype=bool)
MAX_PIXEL = (1 << 16) - 1
# print("Image type %r recognized." % img.mode)
elif img.mode in 'LP':
print("Errored on", name)
print(("Image type %r recognized, but this program is not written" +
"for an 8-bit image.") % img.mode)
print("Unsure how to proceed; exiting.")
exit(1)
else:
print("Errored on", name)
print("Image type %r recognized, but not a 0-255 grayscale image." % img.mode)
print("Unsure how to proceed; exiting.")
exit(4)
if args.limits is None:
inputs.append(list(image_iter(img)))
else:
inputs.append([im.crop(args.limits) for im in image_iter(img)])
def renorm_bin(arr, thresh, upper):
float_arr = np.asarray(arr, dtype=np.float)
normed = float_arr / upper_thresh
np.clip(normed, 0, 1, out=normed)
binned = arr > thresh
return normed, binned
def arr_to_img(arr):
return Image.fromarray(np.uint8(arr * 255))
try:
img = Image.open(str(args.input))
except FileNotFoundError as e:
print(e)
exit(2)
except OSError as e:
print(e)
exit(3)
if img.mode not in 'LP':
print("Image type %s recognized, but not a 0-255 grayscale image." % img.mode)
print("Unsure how to proceed; exiting.")
exit(1)
img_list = (
list(image_iter(img))
if args.limits is None else
[im.crop(args.limits) for im in image_iter(img)])
cyans_unnormalized = img_list[::2]
yellows_unnormalized = img_list[1::2]
hists = cyan_hist, yellow_hist = [
np.sum([im.histogram() for im in img_list], axis=0)
for img_list in (cyans_unnormalized, yellows_unnormalized)
]
def to_arr_lists(img_list, thresh, upper_thresh):
thresh, upper_thresh, lst, bin_lst = renormalize_all(
img_list, thresh, upper_thresh)
arrs = np.asarray([np.asarray(im) for im in lst], dtype=float) / MAX_PIXEL
