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| ''' | |
| author : OzlemAkgunoglu | |
| github : https://github.com/OzlemAkgunoglu | |
| Dynamic Photo Filter App | |
| This is a Dynamic Photo Filter App that allows you to apply various filters to your images. | |
| Adjust brightness, contrast, sharpening, and select a filter for real-time changes. | |
| And this app is created using OpenCV and Gradio. Thank you for using it. ''' | |
| #Let's load the necessary libraries | |
| import cv2 as cv #OpenCV for image processing | |
| import numpy as np #Numpy for arrays | |
| import gradio as gr #Gradio for UI | |
| # Let's define the filter functions | |
| def apply_grayscale(image): | |
| return cv.cvtColor(image, cv.COLOR_BGR2GRAY) #Convert the image to grayscale | |
| #Sepia filter function | |
| def apply_sepia(image): | |
| sepia_filter = np.array([[0.272, 0.534, 0.131], | |
| [0.349, 0.686, 0.168], | |
| [0.393, 0.769, 0.189]]) | |
| sepia_image = cv.transform(image, sepia_filter) #Apply the filter | |
| return np.clip(sepia_image, 0, 255).astype(np.uint8) #clip to hold values between 0 and 255 prevent excessive brightness or darkening. | |
| def apply_negative(image): | |
| return cv.bitwise_not(image) #Invert the image | |
| #sketch filter | |
| '''Apply Gaussian blur to decrease the noise | |
| and remove unwanted details in the image for better sketch effect ''' | |
| def apply_sketch(image): | |
| gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY) #Convert the image to grayscale | |
| inv = cv.bitwise_not(gray) #Invert the grayscale image | |
| blurred = cv.GaussianBlur(inv, (21, 21), sigmaX=0, sigmaY=0) | |
| sketch_image = cv.divide(gray, 255 - blurred, scale=256) | |
| # divide= gray / (255 - blurred) Normalizes the division result to prevent overly high values by scaling with 256 | |
| return sketch_image | |
| def apply_sharpen(image, sharpening): | |
| sharpening_filter = np.array([[0, -1, 0], | |
| [-1, 5 + sharpening, -1], | |
| [0, -1, 0]]) | |
| return cv.filter2D(image, -1, sharpening_filter) #Apply the filter each pixel is multiplied by the value in the kernel | |
| def apply_edge_detection(image): | |
| return cv.Canny(image, 100, 200) | |
| 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 cv.transform(frame, fall_filter) | |
| # Dictionary to map filter names to functions | |
| filter_functions = { | |
| "Grayscale": apply_grayscale, | |
| "Sepia": apply_sepia, | |
| "Negative": apply_negative, | |
| "Sketch": apply_sketch, | |
| "Sharpen": apply_sharpen, | |
| "Edge Detection": apply_edge_detection, | |
| "Fall": apply_fall_filter | |
| } | |
| # Main function to apply selected filters | |
| def apply_filters(image, filter_type, brightness, contrast, sharpening): | |
| if image is None: | |
| print("Input image is empty!") #for debugging | |
| return None # Return None if the input image is empty | |
| # Adjust brightness and contrast | |
| image = cv.convertScaleAbs(image, alpha=contrast, beta=brightness) | |
| #for debugging | |
| #print("Image after brightness and contrast adjustment:", image) | |
| # Apply the selected filter from dictionary called filter_functions in line 53 | |
| if filter_type in filter_functions: | |
| if filter_type == "Sharpen": | |
| image = filter_functions[filter_type](image, sharpening) # Calls the Sharpen filter with the sharpening parameter for custom sharpening level | |
| else: | |
| image = filter_functions[filter_type](image) | |
| return image | |
| # Define Interface | |
| with gr.Blocks() as app: | |
| # Title and Description | |
| gr.Markdown("<h1 style='text-align: center;'>Dynamic Photo Filter App</h1>") | |
| gr.Markdown("This app allows you to apply various filters to your images. Adjust brightness, contrast, sharpening, and select a filter for real-time changes.") | |
| # Choices and Sliders at the Top | |
| with gr.Row(): | |
| filter_choice = gr.Radio(["Original", "Grayscale", "Sketch", "Sepia", "Negative", "Sharpen", "Edge Detection","Fall"],label="Filter") | |
| with gr.Column(): | |
| brightness_slider = gr.Slider(-100, 100, step=1, label="Brightness", value=0) | |
| contrast_slider = gr.Slider(0.5, 3.0, step=0.1, label="Contrast", value=1.0) | |
| sharpening_slider = gr.Slider(0, 5, step=0.1, label="Sharpening", value=0) | |
| # Horizontal display of the images | |
| with gr.Row(): | |
| image_input = gr.Image(label="Upload Image", type="numpy") | |
| image_output = gr.Image(label="Filtered Image") | |
| # Link events for real-time updates | |
| image_input.change(apply_filters, inputs=[image_input, filter_choice, brightness_slider, contrast_slider, sharpening_slider], outputs=image_output) | |
| filter_choice.change(apply_filters, inputs=[image_input, filter_choice, brightness_slider, contrast_slider, sharpening_slider], outputs=image_output) | |
| brightness_slider.change(apply_filters, inputs=[image_input, filter_choice, brightness_slider, contrast_slider, sharpening_slider], outputs=image_output) | |
| contrast_slider.change(apply_filters, inputs=[image_input, filter_choice, brightness_slider, contrast_slider, sharpening_slider], outputs=image_output) | |
| sharpening_slider.change(apply_filters, inputs=[image_input, filter_choice, brightness_slider, contrast_slider, sharpening_slider], outputs=image_output) | |
| app.launch(share=True) |