Update app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+import cv2
+import numpy as np
+
+def apply_filter(image, filter_type):
+    # 필터에 따라 처리
+    if filter_type == "Soft Glow":
+        image = cv2.GaussianBlur(image, (15, 15), 0)
+        image = cv2.addWeighted(image, 1.5, cv2.GaussianBlur(image, (5, 5), 0), -0.5, 0)
+    elif filter_type == "Portrait Enhancer":
+        lab = cv2.cvtColor(image, cv2.COLOR_BGR2LAB)
+        l, a, b = cv2.split(lab)
+        l = cv2.equalizeHist(l)
+        enhanced = cv2.merge((l, a, b))
+        image = cv2.cvtColor(enhanced, cv2.COLOR_LAB2BGR)
+    elif filter_type == "Warm Tone":
+        warm_filter = np.array([[[20, 10, 0]]], dtype=np.uint8)
+        image = cv2.add(image, warm_filter)
+    elif filter_type == "Cold Tone":
+        cold_filter = np.array([[[-10, 0, 20]]], dtype=np.uint8)
+        image = cv2.add(image, cold_filter)
+    elif filter_type == "High-Key":
+        image = cv2.addWeighted(image, 1.5, np.zeros_like(image, image.dtype), 0, 50)
+    elif filter_type == "Low-Key":
+        image = cv2.addWeighted(image, 0.8, np.zeros_like(image, image.dtype), 0, -50)
+    elif filter_type == "Haze":
+        haze_filter = cv2.GaussianBlur(image, (25, 25), 10)
+        image = cv2.addWeighted(image, 0.8, haze_filter, 0.2, 0)
+    return image
+
+def convert_and_save(image, filter_type):
+    # 필터 적용
+    filtered_image = apply_filter(image, filter_type)
+    # 이미지를 흑백으로 변환
+    gray_image = cv2.cvtColor(filtered_image, cv2.COLOR_BGR2GRAY)
+    output_path = "output.jpg"
+    cv2.imwrite(output_path, gray_image)
+    return gray_image, output_path
+
+# Gradio 인터페이스 정의
+iface = gr.Interface(
+    fn=convert_and_save, 
+    inputs=[
+        gr.Image(label="이미지 업로드"), 
+        gr.Radio(["Soft Glow", "Portrait Enhancer", "Warm Tone", "Cold Tone", "High-Key", "Low-Key", "Haze"], label="필터 선택")
+    ], 
+    outputs=["image", "file"], 
+    title="이미지 흑백 변환기",
+    description="이미지를 업로드하고 필터를 선택한 후 흑백으로 변환된 이미지를 다운로드할 수 있습니다."
+)
+
+if __name__ == "__main__":
+    iface.launch()