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| 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() |