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import cv2
import numpy as np
import gradio as gr
# Farklı filtre fonksiyonları
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 apply_grayscale_filter(frame):
return cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Filtre uygulama fonksiyonu
def apply_filter(filter_type, input_image=None):
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":
return apply_gaussian_blur(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"],
value="Gaussian Blur"
)
interactive=True
# 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], outputs=output_image)
# Gradio arayüzünü başlat
demo.launch()
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