Digits and marks recognition 2 #78
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ferrine
requested changes
May 20, 2020
| from PIL import Image, ImageDraw | ||
| import numpy as np | ||
| import matplotlib.pyplot as plt | ||
| from keras.models import model_from_json |
| import numpy as np | ||
| import matplotlib.pyplot as plt | ||
| from keras.models import model_from_json | ||
| model = model_from_json(open("models/mnist_mega_model_4_sep_1_7.json").read()) |
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Собственно говоря, тут обновленная единая модель, которая выдает 12 классов.
0-9 цифры, 10–пустота, 11 –галочка/крестик.
В отличие от базовой модели она чувствительная. Какая-то ахинея (закрашивание/кружочек/стрелочка) не будут опознаны как крестик. Хорошо опознаются нормальные крестики + нормальные галочки (в т.ч. и повернутые).
По-хорошему, надо оставить и обратную совместимость к старой модели.
Качество отдельно на цифрах ~0.998 на тестовой MNIST выборке.