Update app.py

app.py

@@ -14,7 +14,6 @@ def apply_filter(image, filter_type, intensity):
     if filter_type == "Grayscale":
         return convert_to_grayscale(image)
     elif filter_type == "Soft Glow":
-        # 기본 10% 강도에서 시작하여 최대 100% 강도까지 조절
         base_intensity = 0.1
         adjusted_intensity = base_intensity + (normalized_intensity * (1 - base_intensity))
         
@@ -22,30 +21,25 @@ def apply_filter(image, filter_type, intensity):
         soft_glow = cv2.addWeighted(image, 1 - adjusted_intensity, gaussian, adjusted_intensity, 0)
         return soft_glow
     elif filter_type == "Portrait Enhancer":
-        # 기본 50% 강도에서 시작하여 최대 100% 강도까지 조절
         base_intensity = 0.5
         adjusted_intensity = base_intensity + (normalized_intensity * (1 - base_intensity))
         
-        image_pil = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+        image_pil = Image.fromarray(image)
         
         enhancer = ImageEnhance.Sharpness(image_pil)
-        image_pil = enhancer.enhance(1 + 0.5 * adjusted_intensity)  # 강도 반영
+        image_pil = enhancer.enhance(1 + 0.5 * adjusted_intensity)
         
         enhancer = ImageEnhance.Color(image_pil)
-        image_pil = enhancer.enhance(1 + 0.5 * adjusted_intensity)  # 강도 반영
+        image_pil = enhancer.enhance(1 + 0.5 * adjusted_intensity)
         
-        enhanced_image = cv2.cvtColor(np.array(image_pil), cv2.COLOR_RGB2BGR)
+        enhanced_image = np.array(image_pil)
         return enhanced_image
     elif filter_type == "Warm Tone":
-        # 따뜻한 톤 적용
-        warm_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-        warm_image = cv2.applyColorMap(warm_image, cv2.COLORMAP_AUTUMN)
-        return cv2.cvtColor(warm_image, cv2.COLOR_RGB2BGR)
+        warm_image = cv2.applyColorMap(image, cv2.COLORMAP_AUTUMN)
+        return warm_image
     elif filter_type == "Cold Tone":
-        # 차가운 톤 적용
-        cold_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-        cold_image = cv2.applyColorMap(cold_image, cv2.COLORMAP_WINTER)
-        return cv2.cvtColor(cold_image, cv2.COLOR_RGB2BGR)
+        cold_image = cv2.applyColorMap(image, cv2.COLORMAP_WINTER)
+        return cold_image
     elif filter_type == "High-Key":
         high_key = cv2.convertScaleAbs(image, alpha=1.0 + 0.8 * normalized_intensity, beta=30)
         return high_key
@@ -60,14 +54,15 @@ def apply_filter(image, filter_type, intensity):
 
 def convert_to_grayscale(image):
     gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    return cv2.cvtColor(gray_image, cv2.COLOR_GRAY2BGR)  # 필터 적용 후 일관성을 위해 BGR로 변환
+    return cv2.cvtColor(gray_image, cv2.COLOR_GRAY2BGR)
 
 def convert_and_save(image, filter_type, intensity):
-    filtered_image = apply_filter(image, filter_type, intensity)
+    image_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    filtered_image = apply_filter(image_cv, filter_type, intensity)
     
-    # numpy array를 PIL 이미지로 변환
-    original_image_pil = Image.fromarray(cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR))
-    filtered_image_pil = Image.fromarray(filtered_image)
+    # 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))
 
     return original_image_pil, filtered_image_pil  # 원본과 필터 적용된 이미지를 반환