def show_shear(sent):
she = 7
img = ochre.get_sentence(sent)
img_ = ochre.generators.shear(ochre.get_sentence(sent), shearing=she)
img = np.concatenate((img, img_), axis=1)
img_ = ochre.generators.shear(ochre.get_sentence(sent), shearing=-she)
img = np.concatenate((img, img_), axis=1)
plt.imshow(img)
plt.show()
def show_shift(sent):
shi = 2 # number of shifts each direction
img = ochre.get_sentence(sent)
for i in range(shi * 2):
img_ = ochre.generators.shift(ochre.get_sentence(sent), 2 * (i - shi),
0)
img = np.concatenate((img, img_), axis=1)
for i in range(shi * 2):
img_ = ochre.generators.shift(ochre.get_sentence(sent), 0,
2 * (i - shi))
img = np.concatenate((img, img_), axis=1)
plt.imshow(img)
plt.show()
def main(sentence, collection=True):
print(sentence)
box = lambda idx: (0, idx * 14, 14, (idx + 1) * 14)
sentence_img = ochre.get_sentence(sentence)
letters = sorted(set(sentence.replace(" ", "")))
if collection:
ts = {
c: list(ochre.collection.collection(ochre.get_letter(c)))
for c in letters
}
else:
ts = {c: [ochre.get_letter(c)] for c in letters}
nn = ochre.training.train(ts)
prediction = [
ochre.training.predict(nn, sentence_img, box=box(idx))
for idx in range(len(sentence))
]
print("".join(prediction))
for idx, c in enumerate(sentence):
if c == " ":
print(f"Skipping space at idx={idx}")
continue
letter = ochre.training.predict(nn, sentence_img, box=box(idx))
cor = "ok" if letter == c else "fail"
print(f"{letter} == {c} {cor}")
def test_sentence():
box = lambda idx: (0, idx * 14, 14, (idx + 1) * 14)
sentence = "my first word".lower()
sentence_img = ochre.get_sentence(sentence)
letters = sorted(set(sentence.replace(" ", "")))
nn = _get_nn(letters)
for idx, c in enumerate(sentence):
if c == " ":
print(f"Skipping space at idx={idx}")
continue
letter = ochre.training.predict(nn, sentence_img, box=box(idx))
assert letter == c
def vis_sentence(sent):
coll = list(
ochre.collection.collection(
ochre.get_sentence(sent, serif=os.getenv("SERIF"))))
return coll