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superres.py
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import tensorflow as tf
import numpy as np
import cv2
from mss import mss
from PIL import Image
import time
import platform
if platform.system()=='Windows':
from win32 import win32gui
from ctypes import windll
import win32ui
else:
from Xlib.display import Display
disp = Display()
root = disp.screen().root
def get_absolute_geometry(win):
geom = win.get_geometry()
(x, y) = (geom.x, geom.y)
w,h=(geom.width, geom.height)
while True:
parent = win.query_tree().parent
pgeom = parent.get_geometry()
x += pgeom.x
y += pgeom.y
#print (w,h)
if parent.id == root.id:
break
w=pgeom.width
h=pgeom.height
win = parent
return (x, y, w+x, h+y)
def getbackgroundwindowimage(hwnd, sx, sy):
left, top, right, bot = win32gui.GetWindowRect(hwnd)
w = right - left
h = bot - top
hwndDC = win32gui.GetWindowDC(hwnd)
mfcDC = win32ui.CreateDCFromHandle(hwndDC)
saveDC = mfcDC.CreateCompatibleDC()
saveBitMap = win32ui.CreateBitmap()
saveBitMap.CreateCompatibleBitmap(mfcDC, w-sx, h-sy)
saveDC.SelectObject(saveBitMap)
# Change the line below depending on whether you want the whole window
# or just the client area.
result = windll.user32.PrintWindow(hwnd, saveDC.GetSafeHdc(), 1)
#result = windll.user32.PrintWindow(hwnd, saveDC.GetSafeHdc(), 0)
bmpinfo = saveBitMap.GetInfo()
bmpstr = saveBitMap.GetBitmapBits(True)
im = Image.frombuffer(
'RGB',
(bmpinfo['bmWidth'], bmpinfo['bmHeight']),
bmpstr, 'raw', 'BGRX', 0, 1)
win32gui.DeleteObject(saveBitMap.GetHandle())
saveDC.DeleteDC()
mfcDC.DeleteDC()
win32gui.ReleaseDC(hwnd, hwndDC)
return im
tf.keras.backend.set_floatx('float16')
rgb_mean = np.array([0.4488, 0.4371, 0.4040]) * 255
def normalize(x, rgb_mean=rgb_mean):
return (x - rgb_mean) / 127.5
def denormalize(x, rgb_mean=rgb_mean):
return x * 127.5 + rgb_mean
inp=tf.keras.layers.Input((None,None,3))
x=tf.keras.layers.Lambda(normalize)(inp)
x0=tf.keras.layers.Conv2D(64,3,padding='same')(x)
x=x0
for i in range(4):
y=tf.keras.layers.Conv2D(64,3,activation='relu',padding='same')(x)
y=tf.keras.layers.Conv2D(64,3,padding='same')(y)
x=tf.keras.layers.Add()([x,y])
x=tf.keras.layers.Conv2D(64,3,padding='same')(x)
x=tf.keras.layers.Add()([x0,x])
x=tf.keras.layers.Conv2D(48,3,padding='same')(x)
x=tf.keras.layers.Lambda (lambda z: tf.nn.depth_to_space(z, 4))(x)
out=tf.keras.layers.Lambda(denormalize)(x)
rtsrn=tf.keras.models.Model(inputs=inp, outputs=out)
rtsrn.load_weights('RTSR_NEAREST.h5')
rtsrm=tf.keras.models.clone_model(rtsrn)
rtsrm.load_weights('RTSR_MEDIAN.h5')
inp=rtsrn.input
out=tf.keras.backend.clip(rtsrn.output, 0, 255)
myclippededsrn=tf.keras.models.Model(inputs=inp, outputs=tf.cast(out, tf.uint8))
inp=rtsrm.input
out=tf.keras.backend.clip(rtsrm.output, 0, 255)
myclippededsrm=tf.keras.models.Model(inputs=inp, outputs=tf.cast(out, tf.uint8))
for i in range(7,0,-1):
time.sleep(1)
print ('make Game Window active for capturing, {} s. remains'.format(i))
if platform.system()=='Windows':
hwnd = win32gui.GetForegroundWindow()
windname=win32gui.GetWindowText(hwnd)
else:
hwnd = disp.get_input_focus().focus
pixels=[2,2]
shiftzero=[0,0]
windowsize=[0,0]
FPS=10.0
enhance=False
sct=mss()
resizemode=0
while True:
starttime=time.time()
if platform.system()=='Windows':
dimensions = win32gui.GetWindowRect(hwnd)
#region=(dimensions[0]//8*8+shiftzero[0],dimensions[1]//8*8+shiftzero[1]+32,dimensions[2]//8*8+shiftzero[0]+windowsize[0],dimensions[3]//8*8+shiftzero[1]+windowsize[1]+32)
screen=getbackgroundwindowimage(hwnd, shiftzero[0], shiftzero[1])
imageinit=np.array(screen).copy()[:,:,::-1]
else:
dimensions=get_absolute_geometry(hwnd)
region=(dimensions[0]//8*8+shiftzero[0],dimensions[1]//8*8+shiftzero[1]+32,dimensions[2]//8*8+shiftzero[0]+windowsize[0],dimensions[3]//8*8+shiftzero[1]+windowsize[1]+32)
screen=sct.grab(region)
imageinit=np.array(screen).copy()[:,:,:3]
#if (pixels[1]==2):
if enhance==0:
img3=np.array(Image.fromarray(imageinit).resize((imageinit.shape[1]*4//pixels[1],imageinit.shape[0]*4//pixels[0]),Image.NEAREST))
if enhance==1:
img2 = np.array(Image.fromarray(imageinit).resize((imageinit.shape[1]//pixels[1],imageinit.shape[0]//pixels[0]),Image.NEAREST))
img3=myclippededsrm.predict(np.expand_dims(img2, 0))[0]
if enhance==2:
img2 = np.array(Image.fromarray(imageinit).resize((imageinit.shape[1]//pixels[1],imageinit.shape[0]//pixels[0]),Image.NEAREST))
img3=myclippededsrn.predict(np.expand_dims(img2, 0))[0]
img4=img3#.astype(np.uint8)
#if resizemode==1:
# img5 = np.array(Image.fromarray(img4).resize((displaydims[0]-50,displaydims[1]-50)))
if resizemode==0:
img5=img4
cv2.putText(img5,'FPS {:.2f} SR {}'.format(FPS, enhance),(30,30),cv2.FONT_HERSHEY_PLAIN, 1,(0,0,255),thickness=1)
cv2.imshow('RTSR', img5)
k = cv2.waitKey(1)
if k == ord('0'):
enhance=(enhance+1)%3
if k == ord('1'):
pixels[1]=1
pixels[0]=1
if k == ord('2'):
pixels[1]=2
pixels[0]=2
if k == ord('r'):
resizemode=1-resizemode
if k == ord('w'):
shiftzero[1]=shiftzero[1]+1
if k == ord('s'):
shiftzero[1]=shiftzero[1]-1
if k == ord('a'):
shiftzero[0]=shiftzero[0]+1
if k == ord('d'):
shiftzero[0]=shiftzero[0]-1
if k == ord('k'):
windowsize[1]=windowsize[1]+8
if k == ord('i'):
windowsize[1]=windowsize[1]-8
if k == ord('j'):
windowsize[0]=windowsize[0]+8
if k == ord('l'):
windowsize[0]=windowsize[0]-8
if k == ord('q'):
cv2.destroyAllWindows()
break
FPS=1/(time.time()-starttime)