Update app.py

app.py

@@ -29,10 +29,10 @@ def apply_filter(image, filter_type, intensity):
         image_pil = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
         
         enhancer = ImageEnhance.Sharpness(image_pil)
-        image_pil = enhancer.enhance(1 + 0.1 * adjusted_intensity)
+        image_pil = enhancer.enhance(1 + 0.5 * adjusted_intensity)  # 강도 반영
         
         enhancer = ImageEnhance.Color(image_pil)
-        image_pil = enhancer.enhance(1 + 0.1 * adjusted_intensity)
+        image_pil = enhancer.enhance(1 + 0.5 * adjusted_intensity)  # 강도 반영
         
         enhanced_image = cv2.cvtColor(np.array(image_pil), cv2.COLOR_RGB2BGR)
         return enhanced_image
@@ -47,13 +47,13 @@ def apply_filter(image, filter_type, intensity):
         cold_image = cv2.applyColorMap(cold_image, cv2.COLORMAP_WINTER)
         return cv2.cvtColor(cold_image, cv2.COLOR_RGB2BGR)
     elif filter_type == "High-Key":
-        high_key = cv2.convertScaleAbs(image, alpha=1.0 + 0.2 * normalized_intensity, beta=30)
+        high_key = cv2.convertScaleAbs(image, alpha=1.0 + 0.8 * normalized_intensity, beta=30)
         return high_key
     elif filter_type == "Low-Key":
-        low_key = cv2.convertScaleAbs(image, alpha=1.0 - 0.3 * normalized_intensity, beta=-30)
+        low_key = cv2.convertScaleAbs(image, alpha=1.0 - 0.7 * normalized_intensity, beta=-30)
         return low_key
     elif filter_type == "Haze":
-        haze = cv2.addWeighted(image, 1.0 - 0.3 * normalized_intensity, np.full(image.shape, 255, dtype=np.uint8), 0.3 * normalized_intensity, 0)
+        haze = cv2.addWeighted(image, 1.0 - 0.7 * normalized_intensity, np.full(image.shape, 255, dtype=np.uint8), 0.3 * normalized_intensity, 0)
         return haze
     else:
         return image