Update app.py

app.py

@@ -5,10 +5,7 @@ from PIL import Image, ImageEnhance
 from gradio_imageslider import ImageSlider
 
 def apply_filter(image, filter_type, intensity):
-    # PIL 이미지를 numpy array로 변환
     image = np.array(image)
-
-    # 강도를 0.0에서 1.0 사이로 정규화
     normalized_intensity = intensity / 100.0
 
     if filter_type == "Grayscale":
@@ -16,42 +13,32 @@ def apply_filter(image, filter_type, intensity):
     elif filter_type == "Soft Glow":
         base_intensity = 0.1
         adjusted_intensity = base_intensity + (normalized_intensity * (1 - base_intensity))
-        
         gaussian = cv2.GaussianBlur(image, (15, 15), 0)
         soft_glow = cv2.addWeighted(image, 1 - adjusted_intensity, gaussian, adjusted_intensity, 0)
         return soft_glow
     elif filter_type == "Portrait Enhancer":
         base_intensity = 0.5
         adjusted_intensity = base_intensity + (normalized_intensity * (1 - base_intensity))
-        
         image_pil = Image.fromarray(image)
-        
         enhancer = ImageEnhance.Sharpness(image_pil)
         image_pil = enhancer.enhance(1 + 0.5 * adjusted_intensity)
-        
         enhancer = ImageEnhance.Color(image_pil)
         image_pil = enhancer.enhance(1 + 0.5 * adjusted_intensity)
-        
         enhanced_image = np.array(image_pil)
         return enhanced_image
     elif filter_type == "Warm Tone":
-        # 강도를 30%로 설정 (따뜻한 톤 적용)
         warm_image = cv2.addWeighted(image, 1.0, np.full(image.shape, (20, 66, 112), dtype=np.uint8), 0.3 * normalized_intensity, 0)
         return warm_image
     elif filter_type == "Cold Tone":
-        # 강도를 30%로 설정 (차가운 톤 적용)
         cold_image = cv2.addWeighted(image, 1.0, np.full(image.shape, (112, 66, 20), dtype=np.uint8), 0.3 * normalized_intensity, 0)
         return cold_image
     elif filter_type == "High-Key":
-        # 강도를 30%로 설정
         high_key = cv2.convertScaleAbs(image, alpha=1.0 + 0.3 * normalized_intensity, beta=20)
         return high_key
     elif filter_type == "Low-Key":
-        # 강도를 10%로 설정
         low_key = cv2.convertScaleAbs(image, alpha=1.0 - 0.1 * normalized_intensity, beta=-10)
         return low_key
     elif filter_type == "Haze":
-        # 강도를 30%로 설정
         haze = cv2.addWeighted(image, 1.0, np.full(image.shape, 255, dtype=np.uint8), 0.3 * normalized_intensity, 0)
         return haze
     else:
@@ -65,15 +52,13 @@ def convert_and_save(image, filter_type, intensity):
     image_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
     filtered_image = apply_filter(image_cv, filter_type, intensity)
     
-    # OpenCV 이미지를 다시 PIL로 변환
     original_image_pil = Image.fromarray(cv2.cvtColor(image_cv, cv2.COLOR_BGR2RGB))
     filtered_image_pil = Image.fromarray(cv2.cvtColor(filtered_image, cv2.COLOR_BGR2RGB))
 
-    # 필터 적용된 이미지를 JPG로 저장
     output_path = "filtered_image.jpg"
     filtered_image_pil.save(output_path)
 
-    return original_image_pil, filtered_image_pil, output_path  # 원본, 필터 적용된 이미지와 파일 경로 반환
+    return [original_image_pil, filtered_image_pil], output_path
 
 def get_filter_description(filter_type):
     descriptions = {