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use image::{DynamicImage, GenericImageView, ImageBuffer, Luma, Rgb};
use crate::kernel::{SeparableKernel};

pub trait Convolution where Self: GenericImageView {
    fn compute_pixel_index(
        &self,
        stride: usize,
        kernel_size: usize,
        kernel_index: isize,
        pixel_index: usize,
        max: usize,
    ) -> u32 {
        let kernel_size = kernel_size as isize;
        let kernel_padding = kernel_size / 2;

        let distance = kernel_index * stride as isize;

        let mut index = pixel_index as isize + distance;

        if index < 0 {
            index = -index;
        } else if index > max as isize - kernel_padding {
            let overshot_distance = index - max as isize + kernel_padding;
            index = max as isize - overshot_distance;
        }

        index as u32
    }

    fn convolve<const KERNEL_SIZE: usize>(
        &mut self,
        kernel: SeparableKernel<KERNEL_SIZE>,
        stride: usize,
    );
}

impl Convolution for ImageBuffer<Luma<f32>, Vec<f32>> {
    fn convolve<const KERNEL_SIZE: usize>(&mut self, kernel: SeparableKernel<KERNEL_SIZE>, stride: usize) {
        let linear_kernel = kernel.values();

        for y in 0..self.height() {
            for x in 0..self.width() {
                let mut pixel_sum = 0.;

                for (kernel_index, value) in linear_kernel.iter().enumerate() {
                    let relative_kernel_index = kernel_index as isize - (KERNEL_SIZE as isize / 2);
                    let pixel_index = self.compute_pixel_index(
                        stride,
                        KERNEL_SIZE,
                        relative_kernel_index,
                        x as usize,
                        self.width() as usize
                    );

                    pixel_sum += self.get_pixel(pixel_index, y).0[0] * value;
                }

                self.put_pixel(x, y, Luma([pixel_sum]));
            }
        }

        for x in 0..self.width() {
            for y in 0..self.height() {
                let mut pixel_sum = 0.;

                for (kernel_index, value) in linear_kernel.iter().enumerate() {
                    let relative_kernel_index = kernel_index as isize - (KERNEL_SIZE as isize / 2);
                    let pixel_index = self.compute_pixel_index(
                        stride,
                        KERNEL_SIZE,
                        relative_kernel_index,
                        y as usize,
                        self.width() as usize
                    );

                    pixel_sum += self.get_pixel(x, pixel_index).0[0] * value;
                }

                self.put_pixel(x, y, Luma([pixel_sum]));
            }
        }
    }
}

impl Convolution for ImageBuffer<Rgb<f32>, Vec<f32>> {
    fn convolve<const KERNEL_SIZE: usize>(&mut self, kernel: SeparableKernel<KERNEL_SIZE>, stride: usize) {
        let linear_kernel = kernel.values();

        for y in 0..self.height() {
            for x in 0..self.width() {
                let mut pixel_sum = [0., 0., 0.];

                for (kernel_index, value) in linear_kernel.iter().enumerate() {
                    let relative_kernel_index = kernel_index as isize - (KERNEL_SIZE as isize / 2);
                    let pixel_index = self.compute_pixel_index(
                        stride,
                        KERNEL_SIZE,
                        relative_kernel_index,
                        x as usize,
                        self.width() as usize
                    );

                    let mut computed_values = self.get_pixel(pixel_index, y).0;
                    computed_values = [computed_values[0] * value, computed_values[1] * value, computed_values[2] * value];

                    pixel_sum = [pixel_sum[0] + computed_values[0], pixel_sum[1] + computed_values[1], pixel_sum[2] + computed_values[2]];
                }

                let [r, g, b] = pixel_sum;
                self.put_pixel(x, y, Rgb([r, g, b]));
            }
        }

        for x in 0..self.width() {
            for y in 0..self.height() {
                let mut pixel_sum = [0., 0., 0.];

                for (kernel_index, value) in linear_kernel.iter().enumerate() {
                    let relative_kernel_index = kernel_index as isize - (KERNEL_SIZE as isize / 2);
                    let pixel_index = self.compute_pixel_index(
                        stride,
                        KERNEL_SIZE,
                        relative_kernel_index,
                        y as usize,
                        self.width() as usize
                    );

                    let mut computed_values = self.get_pixel(x, pixel_index).0;
                    computed_values = [computed_values[0] * value, computed_values[1] * value, computed_values[2] * value];

                    pixel_sum = [pixel_sum[0] + computed_values[0], pixel_sum[1] + computed_values[1], pixel_sum[2] + computed_values[2]];
                }

                let [r, g, b] = pixel_sum;
                self.put_pixel(x, y, Rgb([r, g, b]));
            }
        }
    }
}

impl Convolution for DynamicImage {
    fn convolve<const KERNEL_SIZE: usize>(
        &mut self,
        kernel: SeparableKernel<KERNEL_SIZE>,
        stride: usize,
    ) {
        match self {
            DynamicImage::ImageLuma8(_) |
            DynamicImage::ImageLumaA8(_) |
            DynamicImage::ImageLuma16(_) |
            DynamicImage::ImageLumaA16(_) => {
                let mut image = self.to_luma32f();
                image.convolve(kernel, stride);

                let mut result_img: ImageBuffer<Luma<u16>, Vec<u16>> =
                    ImageBuffer::new(self.width(), self.height());

                for (x, y, pixel) in result_img.enumerate_pixels_mut() {
                    *pixel =
                        Luma([(image.get_pixel(x, y).0[0] * u16::MAX as f32) as u16]);
                }

                *self = DynamicImage::ImageLuma16(result_img);
            }
            DynamicImage::ImageRgb8(_) |
            DynamicImage::ImageRgba8(_) |
            DynamicImage::ImageRgb16(_) |
            DynamicImage::ImageRgba16(_) |
            DynamicImage::ImageRgb32F(_) |
            DynamicImage::ImageRgba32F(_) => {
                let mut image = self.to_rgb32f();
                image.convolve(kernel, stride);

                *self = DynamicImage::ImageRgb32F(image);
            }
            _ => unimplemented!("Not implemented")
        }
    }
}