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()