Update app.py

app.py

@@ -1,23 +1,75 @@
+import gradio as gr
+import cv2
+import numpy as np
+
+def process_image(image, gamma=1.0, brightness=0, contrast=0, saturation=0):
+    # 흑백 변환
+    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    gray_image = cv2.cvtColor(gray_image, cv2.COLOR_GRAY2BGR)
+
+    # 감마 보정
+    gamma_corrected = np.array(255 * (gray_image / 255) ** (1 / gamma), dtype='uint8')
+
+    # 밝기 및 대비 조정
+    adjusted = cv2.convertScaleAbs(gamma_corrected, alpha=1 + contrast / 100, beta=brightness)
+
+    # 채도 조정 (흑백이라 의미 없음, 하지만 처리 구조 포함)
+    hsv_image = cv2.cvtColor(adjusted, cv2.COLOR_BGR2HSV).astype(np.float32)
+    hsv_image[..., 1] *= 1 + saturation / 100
+    hsv_image = np.clip(hsv_image, 0, 255).astype(np.uint8)
+    final_image = cv2.cvtColor(hsv_image, cv2.COLOR_HSV2BGR)
+
+    return final_image
+
+def remove_noise(image):
+    return cv2.fastNlMeansDenoisingColored(image, None, 10, 10, 7, 21)
+
 def sharpen_image(image):
-    # Sharpen the image using a kernel
-    kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
-    sharpened = cv2.filter2D(image, -1, kernel)
-    return sharpened
-
-def denoise_image(image):
-    # Remove noise using GaussianBlur
-    denoised = cv2.GaussianBlur(image, (5, 5), 0)
-    return denoised
-
-def process_image(image):
-    # Convert to grayscale
-    grayscale_image = convert_to_grayscale(image)
-    # Enhance the image
-    enhanced_image = enhance_image(grayscale_image)
-    # Apply sharpening
-    sharpened_image = sharpen_image(enhanced_image)
-    # Apply denoising
-    final_image = denoise_image(sharpened_image)
-    # Save and return the file path
-    file_path = save_image(final_image)
-    return final_image, file_path
+    kernel = np.array([[0, -1, 0], [-1, 5,-1], [0, -1, 0]])
+    return cv2.filter2D(image, -1, kernel)
+
+def enhance_image(image, gamma, brightness, contrast, saturation):
+    denoised = remove_noise(image)
+    sharpened = sharpen_image(denoised)
+    return process_image(sharpened, gamma, brightness, contrast, saturation)
+
+def main(image, gamma, brightness, contrast, saturation):
+    enhanced_image = enhance_image(image, gamma, brightness, contrast, saturation)
+    return enhanced_image
+
+def save_image(image):
+    path = "output.jpg"
+    cv2.imwrite(path, image)
+    return path
+
+# Gradio 인터페이스
+with gr.Blocks() as demo:
+    gr.Markdown("## 분위기 있는 흑백 사진 변환기")
+
+    with gr.Row():
+        image_input = gr.Image(label="이미지 업로드", type="numpy")
+
+    with gr.Row():
+        gamma_slider = gr.Slider(0.1, 3.0, value=1.0, step=0.1, label="감마 보정")
+        brightness_slider = gr.Slider(-100, 100, value=0, step=1, label="밝기 조정")
+        contrast_slider = gr.Slider(-100, 100, value=0, step=1, label="대비 조정")
+        saturation_slider = gr.Slider(-100, 100, value=0, step=1, label="채도 조정")
+
+    with gr.Row():
+        image_output = gr.Image(label="결과 이미지")
+
+    with gr.Row():
+        download_button = gr.File(label="결과 이미지 다운로드")
+
+    def update(image, gamma, brightness, contrast, saturation):
+        processed_image = main(image, gamma, brightness, contrast, saturation)
+        path = save_image(processed_image)
+        return processed_image, path
+
+    demo_func = gr.Interface(
+        fn=update,
+        inputs=[image_input, gamma_slider, brightness_slider, contrast_slider, saturation_slider],
+        outputs=[image_output, download_button]
+    )
+
+    demo.launch()