Update app.py

app.py

@@ -7,60 +7,51 @@ def apply_filter(image, filter_type, intensity):
     normalized_intensity = intensity / 100.0
 
     if filter_type == "Grayscale":
-        # 흑백 변환
         return convert_to_grayscale(image)
     elif filter_type == "Soft Glow":
-        # Soft Glow 효과
         gaussian = cv2.GaussianBlur(image, (15, 15), 0)
         soft_glow = cv2.addWeighted(image, 1 - normalized_intensity, gaussian, normalized_intensity, 0)
         return soft_glow
     elif filter_type == "Portrait Enhancer":
         # 간단한 포트레이트 향상 (부드럽게 조정된 대비 및 밝기)
-        enhanced = cv2.detailEnhance(image, sigma_s=5, sigma_r=0.1 + 0.15 * normalized_intensity)
-        return enhanced
+        enhanced = cv2.detailEnhance(image, sigma_s=5, sigma_r=0.05 + 0.1 * normalized_intensity)
+        # 피부 부드럽게 하기 위해 추가적인 블러 적용
+        smoothed = cv2.bilateralFilter(enhanced, d=9, sigmaColor=75, sigmaSpace=75)
+        return smoothed
     elif filter_type == "Warm Tone":
-        # 따뜻한 톤 효과 (빨강 및 노랑 톤을 강조)
         increase_red = np.array([[1.0 + 0.2 * normalized_intensity, 0.0, 0.0],
                                  [0.0, 1.0, 0.0],
                                  [0.0, 0.0, 1.0 - 0.2 * normalized_intensity]])
         warm_image = cv2.transform(image, increase_red)
         return warm_image
     elif filter_type == "Cold Tone":
-        # 차가운 톤 효과 (파랑 톤을 강조)
         increase_blue = np.array([[1.0 - 0.2 * normalized_intensity, 0.0, 0.0],
                                   [0.0, 1.0, 0.0],
                                   [0.0, 0.0, 1.0 + 0.2 * normalized_intensity]])
         cold_image = cv2.transform(image, increase_blue)
         return cold_image
     elif filter_type == "High-Key":
-        # High-Key 효과 (밝기 증가)
         high_key = cv2.convertScaleAbs(image, alpha=1.0 + 0.2 * normalized_intensity, beta=30)
         return high_key
     elif filter_type == "Low-Key":
-        # Low-Key 효과 (밝기 감소)
         low_key = cv2.convertScaleAbs(image, alpha=1.0 - 0.3 * normalized_intensity, beta=-30)
         return low_key
     elif filter_type == "Haze":
-        # Haze 효과
         haze = cv2.addWeighted(image, 1.0 - 0.3 * normalized_intensity, np.full(image.shape, 255, dtype=np.uint8), 0.3 * normalized_intensity, 0)
         return haze
     else:
         return image
 
 def convert_to_grayscale(image):
-    # 이미지를 흑백으로 변환
     gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     return gray_image
 
 def convert_and_save(image, filter_type, intensity):
-    # 선택한 필터와 강도를 이미지에 적용
     filtered_image = apply_filter(image, filter_type, intensity)
-    # 이미지를 저장
     output_path = "output.jpg"
     cv2.imwrite(output_path, filtered_image)
     return filtered_image, output_path
 
-# Gradio 인터페이스 정의
 iface = gr.Interface(
     fn=convert_and_save, 
     inputs=[