import cv2
import numpy as np
import gradio as gr

# Farklı filtre fonksiyonları
def apply_gaussian_blur(frame, blur_level=1):
    ksize = (2 * blur_level + 1, 2 * blur_level + 1)
    return cv2.GaussianBlur(frame, ksize, 0)

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

def apply_edge_detection(frame):
    return cv2.Canny(frame, 100, 200)

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

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

def adjust_saturation(frame, saturation=1.0):
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV).astype("float32")
    hsv[..., 1] *= saturation
    hsv[..., 1] = np.clip(hsv[..., 1], 0, 255)
    return cv2.cvtColor(hsv.astype("uint8"), cv2.COLOR_HSV2BGR)

def adjust_hue(frame, hue_shift=0):
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    hsv[..., 0] = (hsv[..., 0].astype(int) + hue_shift) % 180
    return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)

def adjust_gamma(frame, gamma=1.0):
    inv_gamma = 1.0 / gamma
    table = (np.array([((i / 255.0) ** inv_gamma) * 255 for i in range(256)])
             .astype("uint8"))
    return cv2.LUT(frame, table)

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

def apply_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=None, alpha=1.0, beta=50, saturation=1.0, hue_shift=0, gamma=1.0, blur_level=1):
    if input_image is not None:
        frame = input_image
    else:
        cap = cv2.VideoCapture(0)
        ret, frame = cap.read()
        cap.release()
        if not ret:
            return "Web kameradan görüntü alınamadı"

    # Seçilen filtreyi uygula
    if filter_type == "Gaussian Blur":
        frame = apply_gaussian_blur(frame, blur_level=blur_level)
    elif filter_type == "Keskinleştir":
        frame = apply_sharpening_filter(frame)
    elif filter_type == "Kenar Algılama":
        frame = apply_edge_detection(frame)
    elif filter_type == "Ters Çevir":
        frame = apply_invert_filter(frame)
    elif filter_type == "Gri Tonlama":
        frame = apply_grayscale_filter(frame)
    elif filter_type == "Sepya":
        frame = apply_sepia_filter(frame)
    elif filter_type == "Sonbahar":
        frame = apply_fall_filter(frame)

    # Tüm filtrelerden bağımsız parametreleri uygula
    frame = adjust_brightness_contrast(frame, alpha=alpha, beta=beta)
    frame = adjust_saturation(frame, saturation=saturation)
    frame = adjust_hue(frame, hue_shift=hue_shift)
    frame = adjust_gamma(frame, gamma=gamma)

    return frame

# Gradio arayüzü
with gr.Blocks() as demo:
    gr.Markdown("# Web Kameradan Canlı Filtreleme")

    # Filtre seçenekleri
    filter_type = gr.Dropdown(
        label="Filtre Seçin",
        choices=["Gaussian Blur", "Keskinleştir", "Kenar Algılama", "Ters Çevir", "Parlaklık/Kontrast", "Doygunluk", "Renk Tonu", "Gama", "Gri Tonlama", "Sepya", "Sonbahar"],
        value="Gaussian Blur"
    )

    # Ayar kaydırıcıları
    alpha_slider = gr.Slider(0.5, 3.0, value=1.0, label="Parlaklık")
    beta_slider = gr.Slider(-100, 100, value=50, label="Kontrast")
    saturation_slider = gr.Slider(0.0, 3.0, value=1.0, label="Doygunluk")
    hue_slider = gr.Slider(-90, 90, value=0, label="Renk Tonu Değişimi")
    gamma_slider = gr.Slider(0.1, 3.0, value=1.0, label="Gama")
    blur_slider = gr.Slider(1, 10, value=1, label="Bulanıklık Seviyesi")

    # Görüntü yükleme alanı
    input_image = gr.Image(label="Resim Yükle", type="numpy")

    # Çıktı için görüntü
    output_image = gr.Image(label="Filtre Uygulandı")

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

    # Butona tıklanınca filtre uygulama fonksiyonu
    apply_button.click(
        fn=apply_filter,
        inputs=[filter_type, input_image, alpha_slider, beta_slider, saturation_slider, hue_slider, gamma_slider, blur_slider],
        outputs=output_image
    )

# Gradio arayüzünü başlat
demo.launch()