# resize image to 28×28 pixels

img = img.resize((28, 28))

# convert rgb to grayscale

img = img.convert('L')

img = ImageOps.invert(img)

img = np.array(img)

# reshaping to support our model input and normalizing

img = img.reshape(1, 28, 28, 1)

img = img / 255.0

# predicting the class

res = model.predict([img])[0]

def __init__(self):

tk.Tk.__init__(self)

self.x = self.y = 0

# Creating elements

self.canvas = tk.Canvas(self, width=300, height=300, bg="white", cursor="cross")

self.label = tk.Label(self, text="Draw .", font=("Helvetica", 48))

self.classify_btn = tk.Button(self, text="Recognise", command=self.classify_handwriting)

self.button_clear = tk.Button(self, text="Clear", command=self.clear_all)

# Grid structure

self.canvas.grid(row=0, column=0, pady=2, sticky=W, )

self.label.grid(row=0, column=1, pady=2, padx=2)

self.classify_btn.grid(row=1, column=1, pady=2, padx=2)

self.button_clear.grid(row=1, column=0, pady=2)

# self.canvas.bind("<Motion>", self.start_pos)

self.canvas.bind("<B1-Motion>", self.draw_lines)

def clear_all(self):

self.canvas.delete("all")

def classify_handwriting(self):

HWND = self.canvas.winfo_id() # get the handle of the canvas

rect = win32gui.GetWindowRect(HWND) # get the coordinate of the canvas

a, b, c, d = rect

rect = (a + 4, b + 4, c - 4, d - 4)

im = ImageGrab.grab(rect)

digit, acc = predict_digit(im)

self.label.configure(text=str(digit) + ', ' + str(int(acc * 100)) + '%')

def draw_lines(self, event):

self.x = event.x

self.y = event.y

r = 8