app.py

import cv2
import numpy as np
import gradio as gr

# Farklı filtre fonksiyonlarını da eklediğim kısım
def apply_gaussian_blur(frame):
    return cv2.GaussianBlur(frame, (15, 15), 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_scale=1.0):
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    hsv[..., 1] = cv2.multiply(hsv[..., 1], saturation_scale)
    return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)

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)

def apply_cartoon_filter(frame):
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray = cv2.medianBlur(gray, 5)
    edges = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 9, 9)
    color = cv2.bilateralFilter(frame, 9, 300, 300)
    cartoon = cv2.bitwise_and(color, color, mask=edges)
    return cartoon

def apply_pencil_sketch_filter(frame):
    gray, sketch = cv2.pencilSketch(frame, sigma_s=60, sigma_r=0.07, shade_factor=0.05)
    return sketch

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

def apply_hsv_color_change(frame, hue_shift=10):
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    hsv[..., 0] = (hsv[..., 0] + hue_shift) % 180
    return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)

# Filtre uygulama fonksiyonu
def apply_filter(filter_type, input_image=None, alpha=1.0, beta=50, saturation_scale=1.0, hue_shift=10):
    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"

    if filter_type == "Gaussian Blur":
        frame = apply_gaussian_blur(frame)
    elif filter_type == "Sharpen":
        frame = apply_sharpening_filter(frame)
    elif filter_type == "Edge Detection":
        frame = apply_edge_detection(frame)
    elif filter_type == "Invert":
        frame = apply_invert_filter(frame)
    elif filter_type == "Brightness/Contrast":
        frame = adjust_brightness_contrast(frame, alpha=alpha, beta=beta)
    elif filter_type == "Grayscale":
        frame = apply_grayscale_filter(frame)
    elif filter_type == "Sepia":
        frame = apply_sepia_filter(frame)
    elif filter_type == "Sonbahar":
        frame = apply_fall_filter(frame)
    elif filter_type == "Cartoonize":
        frame = apply_cartoon_filter(frame)
    elif filter_type == "Pencil Sketch":
        frame = apply_pencil_sketch_filter(frame)
    elif filter_type == "Emboss":
        frame = apply_emboss_filter(frame)
    elif filter_type == "HSV Color Change":
        frame = apply_hsv_color_change(frame, hue_shift=hue_shift)
    
    # Saturation ayarını uygulama
    frame = adjust_saturation(frame, saturation_scale=saturation_scale)

    return frame

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

    # Filtre seçenekleri burada
    filter_type = gr.Dropdown(
        label="Filtre Seçin",
        choices=["Gaussian Blur", "Sharpen", "Edge Detection", "Invert", "Brightness/Contrast", 
                 "Grayscale", "Sepia", "Sonbahar", "Cartoonize", "Pencil Sketch", "Emboss", "HSV Color Change"],
        value="Gaussian Blur"
    )
    # Ayarlarımızı ekleyelim
    
    # Görüntü yükleme alanımız
    input_image = gr.Image(label="Resim Yükle", type="numpy")

    # Parlaklık ve Kontrast ayarlarımız
    brightness_slider = gr.Slider(label="Parlaklık Ayarı (beta)", minimum=-100, maximum=100, step=1, value=50)
    contrast_slider = gr.Slider(label="Kontrast Ayarı (alpha)", minimum=0.5, maximum=3.0, step=0.1, value=1.0)

    # Saturation ayarımız 
    saturation_slider = gr.Slider(label="Renk Doygunluğu", minimum=0.0, maximum=3.0, step=0.1, value=1.0)

    # HSV renk kaydırma ayarımız
    hue_slider = gr.Slider(label="HSV Renk Kaydırma", minimum=0, maximum=180, step=1, value=10)

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

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

    # Butona tıklanınca filtre uygulama fonksiyonumuz
    apply_button.click(fn=apply_filter, inputs=[filter_type, input_image, contrast_slider, brightness_slider, saturation_slider, hue_slider], outputs=output_image)

# Gradio arayüzünü başlatma kısmı
demo.launch()