import cv2
import numpy as np
import gradio as gr

# Türler at fonksiyonlar
def ag_blur(frame):
    return cv2.GaussianBlur(frame, (15, 15), 0)

def bileteral (frame):
    return cv2.bilateralFilter(frame, 9, 75, 75)

def median_blur(frame):
    return cv2.medianBlur(frame, 5)
def sharpen(frame):
    kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
    return cv2.filter2D(frame, -1, kernel)

def ad_detection(frame):
    return cv2.Canny(frame, 100, 200)
def brightness(frame):
    return cv2.convertScaleAbs(frame, alpha=1.0, beta=50)

def invert(frame):
    return cv2.bitwise_not(frame)

def emboss(frame):
    kernel = np.array([[-2, -1, 0], [-1, 1, 1], [0, 1, 2]])
    return cv2.filter2D(frame, -1, kernel)

def ab_contrast(frame, alpha=1.0, beta=50):
    return cv2.convertScaleAbs(frame, alpha=alpha, beta=beta)

def ag_filter(frame):
    return cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

def sepia_filter(frame):
    sepia_filter = np.array([[0.272, 0.534, 0.131],
                             [0.349, 0.686, 0.168],
                             [0.393, 0.769, 0.189]])
    return cv2.transform(frame, sepia_filter)

def apply_fall_filter(frame):
    fall_filter = np.array([[0.393, 0.769, 0.189],
                            [0.349, 0.686, 0.168],
                            [0.272, 0.534, 0.131]])
    return cv2.transform(frame, fall_filter)

# Filtre uygulama fonksiyonu
def apply_filter(filter_type, input_image):
    frame = input_image if input_image is not None else None

    if frame is None:
        cap = cv2.VideoCapture(0)
        ret, frame = cap.read()
        cap.release()
        if not ret:
            return "Kameradan görüntü alınamadı"

    if filter_type == "Gaussian Blur":
        return ag_blur(frame)
    elif filter_type == "Median Blur":
        return median_blur(frame)
    elif filter_type == "Brightness":
        return brightness(frame)
    elif filter_type == "Bileteral Blur":
        return bileteral(frame)
    elif filter_type == "Sharpen":
        return sharpen(frame)
    elif filter_type == "Edge Detection":
        return ad_detection(frame)
    elif filter_type == "Emboss":
        return emboss(frame)
    elif filter_type == "Invert":
        return invert(frame)
    elif filter_type == "Contrast":
        return ab_contrast(frame, alpha=1.0, beta=50)
    elif filter_type == "Grayscale":
        return ag_filter(frame)
    elif filter_type == "Sepia":
        return sepia_filter(frame)
    elif filter_type == "Sonbahar":
        return apply_fall_filter(frame)

# Gradio 
with gr.Blocks() as demo:
    gr.Markdown("Canlı Kamera ve Resim Yükleyerek Filtre Uygulaması ")

    # Dropdownd filtre seçimi
    filter_type = gr.Dropdown(
        label="1. Filtreyi Seçin",
        choices=["Gaussian Blur","Brightness", "Median Blur", "Bileteral Blur","Emboss", "Sharpen", "Edge Detection", "Invert", "Contrast", "Grayscale", "Sepia", "Sonbahar"],
        value="Gaussian Blur"
    )
    
    # İkinci filtre seçimi
    filter_type2 = gr.Dropdown(
        label="2. Filtreyi Seçin",
        choices=["Gaussian Blur","Brightness","Median Blur", "Bileteral Blur" ,"Emboss", "Sharpen", "Edge Detection", "Invert", "Contrast", "Grayscale", "Sepia", "Sonbahar"],
        value="Gaussian Blur"
    )

    # Girdi resmi
    input_image = gr.Image(label="Resim Yükle", type="numpy")

    # Çıktı resimleri
    output_image = gr.Image(label="1. Filtre Uygulandı")
    output_image2 = gr.Image(label="2. Filtre Uygulandı")

    # Seçilen filtre türlerini gösteren metin alanları
    selected_filter_text = gr.Textbox(label="Seçilen Filtre 1", interactive=False)
    selected_filter_text2 = gr.Textbox(label="Seçilen Filtre 2", interactive=False)

    # Mesaj alanı
    message = gr.Markdown("")
    message2 = gr.Markdown("")  

    # Filtre uygula butonu
    apply_button = gr.Button("Filtreleri Uygula")

    # Butona tıklanınca filtre uygulama fonksiyonu
    def update_output(f1, f2, img):
        out1 = apply_filter(f1, img)
        out2 = apply_filter(f2, img)
        # Mesajı güncelle
        msg = f"Filtreler uygulandı. Teşekkür ederim "
        msg2 = f"Gökay GÖKÇE"

        return out1, out2, f1, f2, msg, msg2

    apply_button.click(
        update_output,
        inputs=[filter_type, filter_type2, input_image],
        outputs=[output_image, output_image2, selected_filter_text, selected_filter_text2, message, message2]
    )

demo.launch()