import gradio as gr
from PIL import Image, ImageOps, ImageFilter
import cv2
import numpy as np

def apply_filter(image, filter_type):
    # Convert PIL image to OpenCV image
    img = np.array(image.convert("RGB"))

    if filter_type == "Grayscale":
        img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
        img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
    elif filter_type == "Invert":
        img = cv2.bitwise_not(img)
    elif filter_type == "Blur":
        img = cv2.GaussianBlur(img, (15, 15), 0)
    elif filter_type == "Edge Detection":
        gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
        edges = cv2.Canny(gray, 100, 200)
        img = cv2.cvtColor(edges, cv2.COLOR_GRAY2RGB)
    
    return Image.fromarray(img)

# Gradio UI
iface = gr.Interface(
    fn=apply_filter,
    inputs=[
        gr.Image(type="pil"),
        gr.Radio(["Grayscale", "Invert", "Blur", "Edge Detection"], label="Choose a filter")
    ],
    outputs=gr.Image(type="pil"),
    title="🖼️ Image Filter App",
    description="Upload an image and apply various filters!"
)

iface.launch()