Update app.py

app.py

@@ -11,7 +11,7 @@ def apply_filter(img):
     img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
 
     # Exposure: Adjust brightness
-    exposure = -0.31  # Negative for darker, positive for brighter
+    exposure = -0.31
     img = cv2.convertScaleAbs(img, alpha=1.0, beta=exposure * 100)
 
     # Contrast
@@ -23,9 +23,10 @@ def apply_filter(img):
     highlights = -100
     shadows = 50
     hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
-    v = hsv[:, :, 2]
-    v = np.clip(v * (1 + shadows / 100.0) + highlights, 0, 255).astype(np.uint8)
-    hsv[:, :, 2] = v
+    v = hsv[:, :, 2].astype(np.float32)
+    v = np.clip(v + highlights, 0, 255)
+    v = np.clip(v + shadows, 0, 255)
+    hsv[:, :, 2] = v.astype(np.uint8)
     img = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
 
     # Whites and Blacks
@@ -35,11 +36,11 @@ def apply_filter(img):
     img = np.clip(img + blacks, 0, 255).astype(np.uint8)
 
     # Temperature and Tint
-    temp = -2  # Blue (+ve) or Yellow (-ve)
-    tint = 2  # Green (-ve) or Magenta (+ve)
+    temp = -2
+    tint = 2
     b, g, r = cv2.split(img)
-    b = np.clip(b + temp, 0, 255).astype(np.uint8)
-    r = np.clip(r + tint, 0, 255).astype(np.uint8)
+    b = np.clip(b + temp * 10, 0, 255).astype(np.uint8)
+    r = np.clip(r + tint * 10, 0, 255).astype(np.uint8)
     img = cv2.merge((b, g, r))
 
     # Vibrance
@@ -54,7 +55,7 @@ def apply_filter(img):
     # Saturation
     saturation = 20
     hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
-    s = hsv[:, :, 1]
+    s = hsv[:, :, 1].astype(np.float32)
     s = np.clip(s * (1 + saturation / 100.0), 0, 255).astype(np.uint8)
     hsv[:, :, 1] = s
     img = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)