Update app.py

app.py

@@ -190,14 +190,6 @@ import numpy as np
 #contrast = cv2.imread("/content/drive/MyDrive/ColabNotebooks/enhance/After_clahe_equalizer_with_gamma.png",0)
 
 #print(original.dtype)
-def psnr(img1, img2, MAX=None):
-    if MAX is None:
-		    MAX = np.iinfo(img1.dtype).max
-    mse = np.mean((img1 - img2) ** 2)
-    if mse == 0:
-        return 100
-    return 20 * math.log10(MAX / math.sqrt(mse))
-
 
 #db = psnr(original, contrast)
 #print(db)
@@ -522,11 +514,20 @@ def ssim(original,predict):
    ssim = tf.image.ssim(original, predict, max_val=1.0, filter_size=11, filter_sigma=1.5, k1=0.01, k2=0.03)
    return ssim
 
-def psnr(Input,Choice):
-  Output = result(Input,Choice)
-  psnr = tf.image.psnr(Input, Output, max_val=255)
-  return psnr
+#def psnr(Input,Choice):
+#  Output = result(Input,Choice)
+#  psnr = tf.image.psnr(Input, Output, max_val=255)
+#  return psnr
 
+def psnr(Input, Choice, MAX=None):
+    Output = result(Input,Choice)
+    if MAX is None:
+		    MAX = np.iinfo(Input.dtype).max
+    mse = np.mean((Input - Output) ** 2)
+    if mse == 0:
+        return 100
+    return 20 * math.log10(MAX / math.sqrt(mse))
+    
 #lst = cv2.imread('/content/drive/MyDrive/ColabNotebooks/enhance/low-sat.jpg')
 #r = result(lst)
 #cv2.imshow(r)