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| import cv2 as cv | |
| import numpy as np | |
| import gradio as gr | |
| # Farklı filtre fonksiyonları | |
| def apply_gaussian_blur(frame): | |
| return cv.GaussianBlur(frame, (15, 15), 0) | |
| def apply_box_blur(frame): | |
| return cv.blur(frame, (5,5)) | |
| def apply_hsv(frame): | |
| return cv.cvtColor(frame, cv.COLOR_BGR2HSV) | |
| def apply_scale_contrast(frame): | |
| return cv.convertScaleAbs(frame , alpha = 1.5 , beta = 0) | |
| def apply_sharpening_filter(frame): | |
| kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, 1, 0]]) | |
| return cv.filter2D(frame, -1, kernel) | |
| def apply_emboss_filter(frame): | |
| kernel = np.array([[-2,-1,0],[-1,1,1],[0,1,2]]) | |
| return cv.filter2D(frame, -1, kernel) | |
| def apply_edge_detection(frame): | |
| return cv.Canny(frame, 100, 200) | |
| def apply_invert_filter(frame): | |
| return cv.bitwise_not(frame) | |
| def adjust_brightness_contrast(frame, alpha=1.0, beta=50): | |
| return cv.convertScaleAbs(frame, alpha=alpha, beta=beta) | |
| def apply_grayscale_filter(frame): | |
| return cv.cvtColor(frame, cv.COLOR_BGR2GRAY) | |
| # Filtre uygulama fonksiyonu | |
| def apply_filter(filter_type, input_image=None): | |
| if input_image is not None: | |
| frame = input_image | |
| else: | |
| cap = cv.VideoCapture(0) | |
| ret, frame = cap.read() | |
| cap.release() | |
| if not ret: | |
| return "Web kameradan görüntü alınamadı" | |
| if filter_type == "Gaussian Blur": | |
| return apply_gaussian_blur(frame) | |
| elif filter_type == "Box Blur": | |
| return apply_box_blur(frame) | |
| elif filter_type == "HSV": | |
| return apply_hsv(frame) | |
| elif filter_type == "Scale Contrast": | |
| return apply_scale_contrast(frame) | |
| elif filter_type == "Emboss Filter": | |
| return apply_emboss_filter(frame) | |
| elif filter_type == "Sharpen": | |
| return apply_sharpening_filter(frame) | |
| elif filter_type == "Edge Detection": | |
| return apply_edge_detection(frame) | |
| elif filter_type == "Invert": | |
| return apply_invert_filter(frame) | |
| elif filter_type == "Brightness": | |
| return adjust_brightness_contrast(frame, alpha=1.0, beta=50) | |
| elif filter_type == "Grayscale": | |
| return apply_grayscale_filter(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", "Sharpen", "Edge Detection", "Invert", "Brightness", "Grayscale", "Box Blur", "HSV", "Scale Contrast", "Emboss Filter"], | |
| value="Gaussian Blur" | |
| ) | |
| # Görüntü yükleme alanı | |
| input_image = gr.Image(label="Resim Yükle", type="numpy") | |
| # Çıktı için görüntü | |
| output_image = gr.Image(label="Filtre Uygulandı") | |
| # Görüntü yüklendiğinde filtre uygulama fonksiyonu | |
| input_image.change(fn=apply_filter, inputs=[filter_type, input_image], outputs=output_image) | |
| # Gradio arayüzünü başlat | |
| demo.launch() | |