103 lines
2.2 KiB
Python
103 lines
2.2 KiB
Python
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import tensorflow as tf
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import numpy as np
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from matplotlib import pyplot as plt
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from PIL import Image, ImageTk
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import tkinter as tk
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import math
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import time
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__put_active = 0
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__take_active = 0
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__img = None
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__cw = None
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def classify_live(m, label):
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global __img, __cw
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m.compile(optimizer = "adam",
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loss = "categorical_crossentropy",
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metrics = ["accuracy"])
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m.load_weights(f"save-{label}.weights.h5")
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r = tk.Tk()
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r.title("Draw!")
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canvas = np.zeros([28, 28])
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__img = Image.fromarray(np.uint8(canvas * 255), "L")
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__cw = ImageTk.PhotoImage(
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__img.resize(size = (504, 504),
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resample = Image.NEAREST))
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l = tk.Label(r, image = __cw)
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lt = tk.Label(r, text = "", font = ("Liberation Sans", 48))
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lt.pack()
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l.pack()
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def clear_array():
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canvas[:][:] = np.zeros([28, 28])
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def mouse_down(ev):
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global __put_active, __take_active
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if ev.num == 1:
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__put_active = 1
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elif ev.num == 2:
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__take_active = 1
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def mouse_up(ev):
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global __put_active, __take_active
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if ev.num == 1:
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__put_active = 0
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elif ev.num == 2:
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__take_active = 0
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def update_img():
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global __img, __cw
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__img = Image.fromarray(np.uint8(canvas * 255), "L")
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__cw = ImageTk.PhotoImage(
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__img.resize(size = (504, 504),
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resample = Image.NEAREST))
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l.configure(image = __cw)
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r.after(50, update_img)
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def update_pred():
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pred = m.predict(canvas.reshape(-1, 784),
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verbose = 0)
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lt.configure(text = np.argmax(pred))
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r.after(300, update_pred)
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def change_pix(ev):
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x = math.floor(ev.x / 18)
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y = math.floor(ev.y / 18)
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if __put_active:
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canvas[y, x] = 1
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elif __take_active:
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canvas[x, y] = 0
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l.bind("<Motion>", change_pix)
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l.bind("<ButtonPress>", mouse_down)
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l.bind("<ButtonRelease>", mouse_up)
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tk.Button(text = "Clear",
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command = clear_array).pack()
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r.after(300, update_pred)
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r.after(50, update_img)
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r.mainloop()
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