BP_DP-xlanro00/src/main.py

"""! @file main.py
    @brief Main file for the application
    @author xlanro00
"""

# Import basic libraries
import argparse as ap
import sys
import json
from os.path import exists

# Libraries for image processing
import numpy as np
import matplotlib.pyplot as plt
#from PIL import Image
import cv2 as cv
from stl import mesh
import math

# Import custom image filter library
import filters as flt


class app:
    def __init__(self):
        # Parse arguments from command line
        self.parse_arguments()

        # List and dict for filters and corresponding parameters
        self.filters = []
        self.params = {}

        # Parse configuration from json config file
        if self.args.config:
            self.config_file, self.preset_name = self.args.config
            self.config = json.load(open(self.config_file))
            self.parse_conf()

        elif self.args.filters:
            print("No config file given, using command line arguments")
            i = 0

            # Otherwise expect filters from command line
            for filter in self.args.filters:
                if filter.find('=') == -1:
                    # if no '=' char in filter, it is a new filter name
                    self.filters.append(filter)
                    i += 1
                    self.params[i] = {}  # create empty dict for params
                else:
                    # else it's a parameter for current filter
                    key, value = filter.split('=')
                    self.params[i][key] = value
                self.parse_params(self.params[i])

        else:
            print("No filters given, saving original image")

        self.input_file = self.args.input_file
        self.output_file = self.args.output_file
        self.dpi = self.args.dpi
        self.mirror = True if self.args.mirror else False

        if exists(self.input_file):
            self.run_filtering()

        else:

            self.error_exit("Input file " + self.input_file +
                            " does not exist")

        if self.args.stl_file:

            # Get stl filename
            self.stl_file = self.args.stl_file[0]

            # Get mode and model parameters
            if self.args.planar:
                self.mode = "2d"

                if len(self.args.stl_file) < 3:
                    self.height_base = 10
                    self.height_line = 2
                    print(
                        "Warning: Too few arguments, using default values (10mm base, 2mm lines)")
                else:
                    self.height_line = float(self.args.stl_file[1])
                    self.height_base = float(self.args.stl_file[2])
                    print("Base height:", self.height_base,
                          "mm, lines depth/height:", self.height_line, "mm")

            else:
                self.mode = "3d"

                if len(self.args.stl_file) < 4:
                    self.height_line = 2
                    self.curv_rate_x = 0.5
                    self.curv_rate_y = 0.5
                    print(
                        "Warning: Too few arguments, using default values (2mm lines, curvature 0.5 on x, 0.5 on y)")
                else:
                    self.height_line = float(self.args.stl_file[1])
                    self.curv_rate_x = float(
                        self.args.stl_file[2])  # finger depth
                    self.curv_rate_y = float(
                        self.args.stl_file[3])  # finger depth
                    # self.curv_rate_x = float(self.args.stl_file[2]) # excentricity x
                    # self.curv_rate_y = float(self.args.stl_file[3]) # excentricity y
                    print("Line height:", self.height_line,"mm, x axis curvature:", self.curv_rate_x,
                         ", y axis curvature:", self.curv_rate_y)

            print(self.mode, "mode selected")
            self.run_stl()

    def parse_arguments(self):
        '''Parse arguments from command line using argparse library.
        '''

        parser = ap.ArgumentParser(prog='main.py',
                                   description='Program for processing a 2D image into 3D fingerprint.',
                                   usage='%(prog)s [-h] [-m | --mirror | --no-mirror] [-p] input_file output_file dpi ([-c config_file preset | --config config_file preset] | [filters ...]) [-s stl_file | --stl stl_file height_line height_base | --stl_file stl_file height_line curv_rate_x curv_rate_y]')

        # positional arguments
        parser.add_argument("input_file", type=str, help="input file path")
        parser.add_argument("output_file", type=str, help="output file path")
        parser.add_argument("dpi", type=int, help="dpi of used scanner")

        # boolean switch argument
        parser.add_argument('-m', '--mirror', type=bool, action=ap.BooleanOptionalAction,
                            help="switch to mirror input image")

        # another boolean switch argument, this time with value, name of the new file and dimensions
        parser.add_argument('-s', '--stl_file', type=str, nargs='*',
                            help="create stl model from processed image")

        # another boolean switch argument, this enables 2d mode
        parser.add_argument('-p', '--planar', type=bool, action=ap.BooleanOptionalAction,
                            help="make stl shape planar instead of curved one")

        # configuration file containing presets, preset name
        # pair argument - give both or none
        parser.add_argument('-c', '--config', nargs=2,
                            help='pair: name of the config file with presets, name of the preset')

        # array of unknown length, all filter names saved inside
        parser.add_argument('filters', type=str, nargs='*',
                            help="list of filter names and their parameters in form [filter_name1 param1=value param2=value filter_name2 param1=value...]")

        self.args = parser.parse_args()

    def parse_params(self, params):
        '''Parse parameters of filters. Set to None if not given.
        They are later set to default values in the filter method apply.
        '''

        # TODO: possibly too bloated, sending all possible params to each filter
        possible_params = {"h", "searchWindowSize", "templateWindowSize",
                           "ksize", "kernel", "sigmaX", "sigmaY",
                           "sigmaColor", "sigmaSpace", "d", "anchor", "iterations",
                           "op", "strength", "amount", "radius", "weight", "channelAxis",
                           "theta", "sigma", "lambda", "gamma", "psi"}

        for key in possible_params:
            if params.get(key) is None:
                params[key] = None
            else:
                params[key] = params[key]

    def parse_conf(self):
        '''Parse configuration file if one was given. 
        Store filters and their parameters.
        '''

        # Find preset in config file
        if self.preset_name in self.config:
            filter_array = self.config[self.preset_name]
            # Iterate over filters in preset, store them and their parameters
            for i, filter in enumerate(range(len(filter_array)), start=1):
                self.filters.append(filter_array[filter]["name"])
                self.params[i] = {}
                for attribute, value in filter_array[filter].items():
                    # Filter name isn't needed in here
                    if attribute != "name":
                        self.params[i][attribute] = value
                self.parse_params(self.params[i])
            print("Loaded preset: " + self.preset_name +
                  " from file: " + self.config_file)
        else:
            self.error_exit("Preset not found")

    def error_exit(self, message):
        '''Print error message and exit.
        '''

        print("ERROR:", message, file=sys.stderr)
        exit(1)

#------------------------- FILTERING -------------------------#

    def run_filtering(self):
        '''Load from input file, store as numpy.array, 
        process image using filters and save to output file.
        '''

        self.img = cv.imread(
            self.input_file, cv.IMREAD_GRAYSCALE).astype(np.uint8)

        self.height, self.width = self.img.shape
        print("Height: " + str(self.height) + " px and width: "
              + str(self.width) + " px", file=sys.stderr)
        size = (self.width/self.dpi, self.height/self.dpi)
        fig = plt.figure(figsize=size, frameon=False, dpi=self.dpi)

        ax = plt.Axes(fig, [0., 0., 1., 1.])
        ax.set_axis_off()
        fig.add_axes(ax)

        if self.mirror is True:
            self.mirror_image()

        # Apply all filters and save image
        self.apply_filters()
        self.save_image(fig, ax)
        plt.close()

    def mirror_image(self):
        '''Mirror image using opencv, should be used if we want a positive model.
        '''

        print("Mirroring image", file=sys.stderr)
        self.img = cv.flip(self.img, 1)  # 1 for vertical mirror

    def apply_filters(self):
        '''Apply filters to image one by one.
        In case none were given, pass and save original image to the output file.
        '''

        if len(self.filters) == 0:
            pass
        else:
            # Apply all filters
            for i, filter_name in enumerate(self.filters):
                # Get filter class from filter.py, use the apply method
                filter = getattr(flt, filter_name)
                filter.apply(self, self.params[i+1])

    def save_image(self, fig, ax):
        '''Save processed image to the output file.
        '''

        print("Saving image to", self.output_file, file=sys.stderr)
        # Colormap must be set to grayscale to avoid color mismatch.
        ax.imshow(self.img, cmap="gray")
        fig.savefig(fname=self.output_file, dpi=self.dpi)

#------------------------- STL GENERATION -------------------------#

    def run_stl(self):
        '''Make heightmap, create mesh and save as stl file.
        '''

        self.prepare_heightmap()

        if self.mode == "2d":
            self.make_stl_planar()

        elif self.mode == "3d":
            self.make_stl_curved()

        else:
            self.error_exit("Mode not supported")

        plt.show()
        print(f"Saving model to ", self.stl_file, file=sys.stderr)
        self.save_stl()

    def prepare_heightmap(self):
        '''Modify image values to get usable height/depth values.
        Check validity of dimension parameters.
        '''

        # TODO: redo, too complicated, add extra params, redo checks

        if self.img.dtype == np.float32 or self.img.dtype == np.float64:
            print("Converting to uint8", file=sys.stderr)
            self.img = self.img * 255
            self.img = self.img.astype(np.uint8)
            print("Creating mesh", file=sys.stderr)

        if self.mode == "2d":
            if self.height_base <= 0:
                self.error_exit("Depth of plate height must be positive")

            if self.height_line + self.height_base <= 0:
                self.error_exit("Line depth must be less than plate thickness")

            # Transform image values to get a heightmap
            self.img = (self.height_base + (1 - self.img/255)
                        * self.height_line)

        if self.mode == "3d":
            # TODO check curvature values and print info
            # TODO: copy pasta code, remove
            # Transform image values to get a heightmap
            self.img = (1 - self.img/255) * self.height_line

    def append_faces(self, faces, c):
        # Function to add faces to the list
        faces.append([c, c + 1, c + 2])
        faces.append([c + 1, c + 3, c + 2])
        return c + 4

    def make_stl_planar(self):
        '''Create mesh from meshgrid.
        Create vertices from meshgrid, add depth values from image.
        Create faces from vertices. Add vectors and faces to the model.

        From wikipedia.org/wiki/STL_(file_format):
        ascii stl format consists of repeating structures:

        facet normal ni nj nk # normal vector
            outer loop
                vertex v1x v1y v1z # vertex 1
                vertex v2x v2y v2z # vertex 2
                vertex v3x v3y v3z # vertex 3
            endloop
        endfacet
        '''

        # This sets the size of stl model and number of subdivisions / triangles
        x = np.linspace(0, self.width * 25.4 / self.dpi, self.width)
        y = np.linspace(0, self.height * 25.4 / self.dpi, self.height)

        self.meshgrid_2d = np.meshgrid(x, y)

        # Add the image matrix to the 2D meshgrid and create 1D array of 3D pointsd
        vertex_arr = np.vstack(list(map(np.ravel, self.meshgrid_2d))).T
        z = (self.img / 10).reshape(-1, 1)
        vertex_arr = np.concatenate((vertex_arr, z), axis=1)

        # Convert 1D array back to matrix of 3D points
        vertex_arr = vertex_arr.reshape(self.height, self.width, 3)

        count = 0
        vertices = []
        faces = []

        # Iterate over all vertices, create faces
        for i in range(self.height - 1):
            for j in range(self.width - 1):

                vertices.append([vertex_arr[i][j]])
                vertices.append([vertex_arr[i][j+1]])
                vertices.append([vertex_arr[i+1][j]])
                vertices.append([vertex_arr[i+1][j+1]])

                count = self.append_faces(faces, count)

        # Add faces for the backside of the lithophane
        null_arr = np.copy(vertex_arr)
        for i in range(self.height):
            for j in range(self.width):
                null_arr[i][j][2] = 0

        # Back side faces
        for i in range(self.height - 1):
            for j in range(self.width - 1):

                vertices.append([null_arr[i][j]])
                vertices.append([null_arr[i+1][j]])
                vertices.append([null_arr[i][j+1]])
                vertices.append([null_arr[i+1][j+1]])

                count = self.append_faces(faces, count)

        # Horizontal side faces
        for i in range(self.height - 1):
            vertices.append([vertex_arr[i][0]])
            vertices.append([vertex_arr[i+1][0]])
            vertices.append([null_arr[i][0]])
            vertices.append([null_arr[i+1][0]])

            count = self.append_faces(faces, count)

            max = self.width - 1

            vertices.append([vertex_arr[i+1][max]])
            vertices.append([vertex_arr[i][max]])
            vertices.append([null_arr[i+1][max]])
            vertices.append([null_arr[i][max]])

            count = self.append_faces(faces, count)

        # Vertical side faces
        for j in range(self.width - 1):
            vertices.append([vertex_arr[0][j+1]])
            vertices.append([vertex_arr[0][j]])
            vertices.append([null_arr[0][j+1]])
            vertices.append([null_arr[0][j]])

            count = self.append_faces(faces, count)

            max = self.height - 1

            vertices.append([vertex_arr[max][j]])
            vertices.append([vertex_arr[max][j+1]])
            vertices.append([null_arr[max][j]])
            vertices.append([null_arr[max][j+1]])

            count = self.append_faces(faces, count)

        # Convert to numpy arrays
        faces = np.array(faces)
        vertices = np.array(vertices)

        # Create the mesh - vertices.shape (no_faces, 3, 3)
        self.stl_lithophane = mesh.Mesh(
            np.zeros(faces.shape[0], dtype=mesh.Mesh.dtype))
        for i, face in enumerate(faces):
            for j in range(3):
                self.stl_lithophane.vectors[i][j] = vertices[face[j], :]

    def make_stl_curved(self):
        '''Map fingerprint to finger model.
        '''

        # TODO: if this is the same as 2D, move to heightmap to reduce duplicate code
        x = np.linspace(0, self.width * 25.4 / self.dpi, self.width)
        y = np.linspace(0, self.height * 25.4 / self.dpi, self.height)

        self.meshgrid_3d = np.meshgrid(x, y)

        # Method 1 - logspace and logarithmic curve
        '''z1 = np.logspace(0, 10, int(np.ceil(self.width / 2)), base=0.7)
        z2 = np.logspace(10, 0, int(np.floor(self.width / 2)), base=0.7)
        ztemp = 5*np.concatenate((z1, z2))

        z = np.array([])
        for i in range(self.height):
            z = np.concatenate((z, ztemp + 25*(((i+50)/20)**(-1/2))))
        z = z.reshape(-1, 1)

        self.img = (self.img / 10).reshape(-1, 1)
        z += self.img'''

        # Method 2 - 2 ellipses
        z = np.array([])
        for x in range(self.width):
            z = np.append(z, np.sqrt(1 - (2*x/self.width - 1)**2)
                            * (self.curv_rate_x**2))
        z = np.tile(z, (self.height, 1))
        for y in range(self.height):
            new = np.sqrt((1 - ((self.height - y)/self.height)**2)
                          * (self.curv_rate_y**2))
            z[y] = z[y] + new
                                  
        # TODO: clip responsivelly
        bottom = z[0][math.floor(self.width/2)]
        #top = self.curv_rate_x**2 + self.curv_rate_y
        #np.clip(z, bottom, top, out=z)
        z = z.reshape(-1, 1)
        self.img = (self.img / 10).reshape(-1, 1)
        z += self.img

        vertex_arr = np.vstack(list(map(np.ravel, self.meshgrid_3d))).T
        vertex_arr = np.concatenate((vertex_arr, z), axis=1)
        vertex_arr = vertex_arr.reshape(self.height, self.width, 3)

        count = 0
        vertices = []
        faces = []
        min_point = 0
        for i in range(self.height - 1):
            if vertex_arr[i][0][2] <= bottom:
                min_point = i

        # Add faces for the backside of the lithophane
        vec_side = (vertex_arr[self.height-1][0][2] -
                    vertex_arr[min_point][0][2]) / (self.height - min_point)
        null_arr = np.copy(vertex_arr)
        for i in range(self.height):
            for j in range(self.width):
                null_arr[i][j][2] = 0
                #null_arr[i][j][2] = bottom + vec_side * i
                # for smaller mesh

        # Iterate over all vertices, create faces
        for i in range(self.height - 1):
            for j in range(self.width - 1):
                if (vertex_arr[i][j][2] <= null_arr[i][j][2]
                    or vertex_arr[i+1][j][2] <= null_arr[i+1][j][2]
                    or vertex_arr[i][j+1][2] <= null_arr[i][j+1][2]
                    or vertex_arr[i+1][j+1][2] <= null_arr[i+1][j+1][2]):
                    continue
                vertices.append([vertex_arr[i][j]])
                vertices.append([vertex_arr[i][j+1]])
                vertices.append([vertex_arr[i+1][j]])
                vertices.append([vertex_arr[i+1][j+1]])

                count = self.append_faces(faces, count)

        # Rotated back side faces
        for i in range(self.height - 1):
            for j in range(self.width - 1):
                if (vertex_arr[i][j][2] <= null_arr[i][j][2]):
                    continue

                vertices.append([null_arr[i][j]])
                vertices.append([null_arr[i+1][j]])
                vertices.append([null_arr[i][j+1]])
                vertices.append([null_arr[i+1][j+1]])

                count = self.append_faces(faces, count)

        # Horizontal side faces
        for i in range(self.height - 1): # right
            #if (vertex_arr[i][0][2] < null_arr[i][0][2]):
            #    continue

            vertices.append([vertex_arr[i][0]])
            vertices.append([vertex_arr[i+1][0]])
            vertices.append([null_arr[i][0]])
            vertices.append([null_arr[i+1][0]])

            count = self.append_faces(faces, count)

        for i in range(self.height - 1): # left
            max = self.width - 1
            #if (vertex_arr[i][max][2] < null_arr[i][max][2]):
            #    continue

            vertices.append([vertex_arr[i+1][max]])
            vertices.append([vertex_arr[i][max]])
            vertices.append([null_arr[i+1][max]])
            vertices.append([null_arr[i][max]])

            count = self.append_faces(faces, count)

        # Vertical side faces
        for j in range(self.width - 1): # top
            #if (vertex_arr[0][j][2] < null_arr[0][j][2]):
            #    continue

            vertices.append([vertex_arr[0][j+1]])
            vertices.append([vertex_arr[0][j]])
            vertices.append([null_arr[0][j+1]])
            vertices.append([null_arr[0][j]])

            count = self.append_faces(faces, count)

        for j in range(self.width - 1): # bottom
            max = self.height - 1
            #if (vertex_arr[max][j][2] < null_arr[max][j][2]):
            #    continue

            vertices.append([vertex_arr[max][j]])
            vertices.append([vertex_arr[max][j+1]])
            vertices.append([null_arr[max][j]])
            vertices.append([null_arr[max][j+1]])

            count = self.append_faces(faces, count)

        # Convert to numpy arrays
        faces = np.array(faces)
        vertices = np.array(vertices)

        # Create the mesh - vertices.shape (no_faces, 3, 3)
        self.mesh_finger = mesh.Mesh(
            np.zeros(faces.shape[0], dtype=mesh.Mesh.dtype))
        for i, face in enumerate(faces):
            for j in range(3):
                self.mesh_finger.vectors[i][j] = vertices[face[j], :]

        # print(self.mesh_finger.normals)

    def save_stl(self):
        '''Save final mesh to stl file.
        '''

        if self.mode == "3d":
            self.mesh_finger.save(self.stl_file)
        else:
            self.stl_lithophane.save(self.stl_file)


# run the application
image = app()