'''
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)