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import io
import base64

try:
    from Tkinter import Tk, Label, Entry, Toplevel, Canvas
except ImportError:
    from tkinter import Tk, Label, Entry, Toplevel, Canvas

from PIL import Image, ImageDraw, ImageTk, ImageFont


BASE64_BACKGROUND = 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'

##################
## First Example
#
root = Tk()

image_file = io.BytesIO(base64.b64decode(BASE64_BACKGROUND))
image = Image.open(image_file)


width, height = image.size
root.geometry("%sx%s"%(width, height))

draw = ImageDraw.Draw(image)

text_x = 55
text_y = 45

text = "Login data"

# Use here a nice ttf font
#   font = ImageFont.truetype("YOUR_FONT.ttf", 12)
#   width_text, height_text = font.getsize(text)
#   draw.text((text_x, text_y), text, fill="white", font=font)

width_text, height_text = draw.textsize(text)
draw.text((text_x, text_y), text, fill="white")


photoimage = ImageTk.PhotoImage(image)
Label(root, image=photoimage).place(x=0,y=0)

entry_pady = 7
Entry(root, background="white").place(x=text_x, y=text_y + height_text +entry_pady)

###################################################
# Another example

toplevel = Toplevel(root)

image_file = io.BytesIO(base64.b64decode(BASE64_BACKGROUND))
image = Image.open(image_file)

photoimage2 = ImageTk.PhotoImage(image)

canvas = Canvas(toplevel,width=width, height=height)
canvas.create_image((0,0), image=photoimage2, anchor="nw")
canvas.create_text((text_x, text_y), text=text, fill="white", anchor="nw")
canvas.pack()

entry = Entry(canvas, background="white")
canvas.create_window((text_x, text_y + height_text +entry_pady), window=entry, anchor="nw")

root.mainloop()

Diff to Previous Revision

--- revision 1 2017-04-12 12:10:47
+++ revision 2 2017-04-12 13:34:23
@@ -2,17 +2,19 @@
 import base64
 
 try:
-    from Tkinter import Tk, Label, Entry
+    from Tkinter import Tk, Label, Entry, Toplevel, Canvas
 except ImportError:
-    from tkinter import Tk, Label, Entry
+    from tkinter import Tk, Label, Entry, Toplevel, Canvas
 
 from PIL import Image, ImageDraw, ImageTk, ImageFont
 
 
 BASE64_BACKGROUND = 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'
 
+##################
+## First Example
+#
 root = Tk()
-root.resizable(width=False, height=False)
 
 image_file = io.BytesIO(base64.b64decode(BASE64_BACKGROUND))
 image = Image.open(image_file)
@@ -29,7 +31,7 @@
 text = "Login data"
 
 # Use here a nice ttf font
-#   font = ImageFont.truetype("YOUR_FONT.ttf", FONT_SIZE)
+#   font = ImageFont.truetype("YOUR_FONT.ttf", 12)
 #   width_text, height_text = font.getsize(text)
 #   draw.text((text_x, text_y), text, fill="white", font=font)
 
@@ -42,4 +44,23 @@
 
 entry_pady = 7
 Entry(root, background="white").place(x=text_x, y=text_y + height_text +entry_pady)
+
+###################################################
+# Another example
+
+toplevel = Toplevel(root)
+
+image_file = io.BytesIO(base64.b64decode(BASE64_BACKGROUND))
+image = Image.open(image_file)
+
+photoimage2 = ImageTk.PhotoImage(image)
+
+canvas = Canvas(toplevel,width=width, height=height)
+canvas.create_image((0,0), image=photoimage2, anchor="nw")
+canvas.create_text((text_x, text_y), text=text, fill="white", anchor="nw")
+canvas.pack()
+
+entry = Entry(canvas, background="white")
+canvas.create_window((text_x, text_y + height_text +entry_pady), window=entry, anchor="nw")
+
 root.mainloop()

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