class MyPaintApp(App):
def build(self):
main_box = BoxLayout()
painter_size = '500dp'
draw_parent = BoxLayout(orientation='vertical',
size_hint_x = None,
width = painter_size
)
labels_box = BoxLayout(orientation='vertical')
main_box.add_widget(draw_parent)
main_box.add_widget(labels_box)
self.painter = MyPaintWidget(self.update_res,
size_hint_y = None,
height = painter_size
)
clearbtn = Button(text='Clear')
clearbtn.bind(on_release=self.clear_canvas)
draw_parent.add_widget(self.painter)
draw_parent.add_widget(clearbtn)
# addbtn = Button(text='add')
# addbtn.bind(on_release=self.add_ev)
# labels_box.add_widget(addbtn)
w_nums = []
for i in range(10):
n_w = NumRes(i)
w_nums.append(NumRes(i))
labels_box.add_widget(n_w)
self.w_nums = w_nums
self.labels_box = labels_box
self.machine = ML((28*28, 16, 16, 10, ))
self.machine.load_weight('weights_m.out')
return main_box
def clear_canvas(self, obj):
self.painter.canvas.clear()
def update_res(self):
self.painter.export_to_png('test.png')
image = Image.open('test.png')
im = np.asarray(image)[..., 3] / 255
f = True
while f:
f = False
if min(im.shape) > 28 and np.sum(im[:, 0]) == 0 and np.sum(im[0, :]) == 0:
# remove first row
im = im[1:, :]
# remove first col
im = im[:, 1:]
f = True
if min(im.shape) > 28 and np.sum(im[:, -1]) == 0 and np.sum(im[-1, :]) == 0:
# remove last row
im = im[:-1, :]
# remove last col
im = im[:, :-1]
f = True
if min(im.shape) > 28 and np.sum(im[:, -1]) == 0 and np.sum(im[0, :]) == 0:
# remove first row
im = im[1:, :]
# remove last col
im = im[:, :-1]
f = True
if min(im.shape) > 28 and np.sum(im[:, 0]) == 0 and np.sum(im[-1, :]) == 0:
# remove last row
im = im[:-1, :]
# remove first col
im = im[:, 1:]
f = True
image = Image.fromarray(np.uint8(im*255)).resize((20, 20, ))
im = np.asarray(image) / 255
for i in range(4):
im = np.insert(im, 0, np.zeros((20)), axis =1)
for i in range(4):
im = np.append(im, np.zeros((20, 1)), axis =1)
for i in range(4):
im = np.insert(im, 0, np.zeros((28)), axis =0)
for i in range(4):
im = np.append(im, np.zeros((1, 28,)), axis =0)
image = Image.fromarray(np.uint8(im*255))
image.save('test.png')
res = self.machine(im.squeeze().reshape(28*28))[-1]
res_dict = {
k: res[k] for k in range(len(res))
}
res_dict = {
k: int(round(v * 100)) for k, v in res_dict.items()
}
res_tup = tuple(sorted(res_dict.items(), key=lambda item: item[1]))
# print(res_dict)
# print(res)
self.labels_box.clear_widgets()
for n, v in reversed(res_tup):
self.w_nums[n].set(v)
self.labels_box.add_widget(self.w_nums[n])
for i in range(20):
plt.imshow(test_data[i][0].reshape((
28,
28,
)))
#%%
from ml import ML
b_machine = ML((
28 * 28,
16,
16,
10,
))
b_machine.load_weight('weights.out')
# b_machine.save_weight('weights.out')
#%%
train_len = 5000
test_len = 10000 if train_len > 10000 else train_len
machine = b_machine.copy()
machine.load_weight('weights_m.out')
machine.train(train_data[:train_len], 80)
# machine.save_weight('weights_m.out')
print()
avg_pos = 0
b_avg_pos = 0
