cours_progra/03nov/main.py

from umage import load, save, show_image
from math import atan2, cos 

def grayscale(img_mat):
    """Transform an image into gray

    :img_mat: image en entree
    :returns: grayscale de limage em entree

    """
    new_matrix = list()
    for row in range(len(img_mat)):
        new_matrix.append(list())
        for column in img_mat[row]:
            _r, _g, _b = column
            gray = round(0.2125 * _r + 0.7154 * _g + 0.0721 * _b)
            new_matrix[row].append((gray, gray, gray))

    return new_matrix

def convolution(img_mat, mat):
    """effectue le passage d'une matrice de convolution sur une image grise
    TODO: image de couleurs

    :img_mat: image en entree
    :mat: matrice de convolution
    :returns: image retouchee

    """

    new_matrix = list()
    for row in range(len(img_mat)):
        new_matrix.append(list())
        for column in range(len(img_mat[row])):
            # _gray = img_mat[row][column][0]
            _sum = 0
            for mat_row in range(len(mat)):
                for mat_column in range(len(mat[mat_row])):
                    diff_row = mat_row - len(mat)//2
                    diff_col = mat_column - len(mat[mat_column])//2
                    if dans_image(img_mat, row+diff_row, column+ diff_col):
                        _sum += mat[mat_row][mat_column] * img_mat[row + diff_row][column + diff_col][0]
            new_matrix[row].append((_sum, _sum, _sum))
    return new_matrix

def dans_image(img_mat, row, col):
    if row < len(img_mat)-1 and row > 0 and col < len(img_mat[0])-1 and col > 0:
        return True
    return False

def calculate_direction(img1, img2):
    """Calculate the image direction of 2 image that has been trough gx and gy of phobels formula

    :img1: x image of fobel 
    :img2: y image of fobel 
    :returns: matrix of direction 

    """
    res = list()
    for row in range(len(img1)):
        res.append(list())
        for col in range(len(img1[row])):
            res[row].append(atan2(img2[row][col][0], img1[row][col][0]))
    return res


def dir_mat_to_img(mat):
    """take a matrix with direction and transform it in image with direction hue """
    res = list()
    for row in range(len(mat)):
        res.append(list())
        for col in range(len(mat[row])):
            res[row].append((round(256*cos(mat[row][col])), round(256*cos(mat[row][col] + 120)), round(256*cos(mat[row][col]  - 120))))
    return res



if __name__ == "__main__":
    unit = [
            [0, 1, 0],
            [0, 0, 0],
            [0, 0, 0]]
    convolution1 = [
            [-1, -1, -1],
            [-1,  8, -1],
            [-1, -1, -1]]
    convolution2 = [
            [-1, -1, -1],
            [-1,  9, -1],
            [-1, -1, -1]]
    convolution3 = [
            [-2, 0, 0],
            [ 0, 1, 0],
            [ 0, 0, 2]]

    phobel1 = [
            [ 1, 0, -1],
            [ 2, 1, -2],
            [ 1, 0, -1]]
    phobel2 = [
            [ 1, 2, 1],
            [ 0, 0, 0],
            [ -1, -2, -1]]

    img = load('./myimg.jpg')
    new_image = grayscale(img)
    convolution(new_image, convolution2)
    phob1_img = convolution(new_image, phobel1)
    phob2_img = convolution(new_image, phobel2)
    final = dir_mat_to_img(calculate_direction(phob2_img, phob1_img))
    save(final, 'final2')