Enhancement

README.md

@@ -1,6 +1,6 @@
 # linedraw
 Convert images to vectorized line drawings for plotters.
-![Alt text](./screenshots/1.png?raw=true "")
+![Alt text](./docs/assets/1.png?raw=true "")
 
 - Exports polyline-only svg file with optimized stroke order for plotters;
 - Sketchy style powered by Perlin noise;
@@ -9,44 +9,57 @@ Convert images to vectorized line drawings for plotters.
 ## Dependencies
 Python 2 or 3, PIL/Pillow, numpy, OpenCV (Optional for better performance)
 
+```shell
+pip install -r requirements.txt
+```
+
 ## Usage
 Convert an image to line drawing and export .SVG format:
 
 ```shell
-$ python linedraw.py -i input.jpg -o output.svg
+python linedraw.py -i input.jpg -o output.svg
 ```
 Command specs:
 
 ```
-usage: linedraw.py [-h] [-i [INPUT_PATH]] [-o [OUTPUT_PATH]] [-b] [-nc] [-nh]
-                   [--no_cv] [--hatch_size [HATCH_SIZE]]
-                   [--contour_simplify [CONTOUR_SIMPLIFY]]
+usage: linedraw.py [-h] [-i [INPUT_PATH]] [-o [OUTPUT_PATH]] [-r [RESOLUTION]] [-b] [-nc] [-nh] [--no-cv] [--hatch-size [HATCH_SIZE]] [--contour-simplify [CONTOUR_SIMPLIFY]] [-v]
+                   [--save-settings]
 
 Convert image to vectorized line drawing for plotters.
 
-optional arguments:
+options:
   -h, --help            show this help message and exit
   -i [INPUT_PATH], --input [INPUT_PATH]
-                        Input path
+                        Input image path
   -o [OUTPUT_PATH], --output [OUTPUT_PATH]
-                        Output path.
-  -b, --show_bitmap     Display bitmap preview.
-  -nc, --no_contour     Don't draw contours.
-  -nh, --no_hatch       Disable hatching.
-  --no_cv               Don't use openCV.
-  --hatch_size [HATCH_SIZE]
+                        Output image path
+  -r [RESOLUTION], --resolution [RESOLUTION]
+                        Resolution of the output image
+  -b, --show-bitmap     Display bitmap preview.
+  -nc, --no-contour     Don't draw contours.
+  -nh, --no-hatch       Disable hatching.
+  --no-cv               Don't use openCV.
+  --hatch-size [HATCH_SIZE]
                         Patch size of hatches. eg. 8, 16, 32
-  --contour_simplify [CONTOUR_SIMPLIFY]
+  --contour-simplify [CONTOUR_SIMPLIFY]
                         Level of contour simplification. eg. 1, 2, 3
+  -v, --visualize       Visualize the output using turtle
+  --save-settings       To Save the settings to a json file
+
 ```
 Python:
 
 ```python
 import linedraw
+
+linedraw.argument.resolution = 512  # set arguments
 lines = linedraw.sketch("path/to/img.jpg")  # return list of polylines, eg.
-                                            # [[(x,y),(x,y),(x,y)],[(x,y),(x,y),...],...]
-                                            
-linedraw.visualize(lines)                   # simulates plotter behavior
-                                            # draw the lines in order using turtle graphics.
+# [[(x,y),(x,y),(x,y)],[(x,y),(x,y),...],...]
+
+linedraw.visualize(lines)  # simulates plotter behavior
+# draw the lines in order using turtle graphics.
 ```
 
+## Future Plans
+1. Rasterised Output
+2. GUI for the tool

line_draw/__init__.py

@@ -0,0 +1 @@
+from line_draw.helper import sketch

line_draw/default.py

@@ -0,0 +1,29 @@
+import json
+
+class Default:
+    export_path = "output/out.svg"
+    show_bitmap = False
+    draw_contours = True
+    draw_hatch = True
+    no_cv = False
+    hatch_size = 16
+    contour_simplify = 2
+    resolution = 1024
+    save_settings = False
+
+    def save(self,settings_path):
+        print("Savings settings to a JSON file")
+        file = open(settings_path, 'w')
+        data = {
+            "resolution": self.resolution,
+            "show_bitmap": self.show_bitmap,
+            "draw_contours": self.draw_contours,
+            "draw_hatch": self.draw_hatch,
+            "use_opencv": not self.no_cv,
+            "hatch_size": self.hatch_size,
+            "contour_simplify": self.contour_simplify
+        }
+        json.dump(data,file)
+        file.close()
+
+argument = Default()

line_draw/helper.py

@@ -0,0 +1,235 @@
+from PIL import Image, ImageOps, ImageDraw
+import line_draw.perlin as perlin
+from datetime import datetime
+import os
+
+from line_draw.filters import appmask, F_SobelX, F_SobelY
+from line_draw.default import argument
+from line_draw.util import distsum, is_image_file, extract_file_name_and_extension
+from line_draw.strokesort import sortlines
+
+
+def sketch(input_path, output_path:str):
+    IMAGE = None
+
+    if not is_image_file(input_path):
+        return print("Please provide the path for an image.")
+
+    out_file, out_ext = extract_file_name_and_extension(output_path)
+
+    if not out_file:
+        in_file, in_ext = extract_file_name_and_extension(input_path)
+        out_ext = '.svg'
+        if not output_path.endswith('/'):
+            output_path += '/'
+        output_path += in_file + out_ext
+
+    if out_ext != '.svg':
+         return print("Currently we can only save as svg file")
+
+    try:
+        IMAGE = Image.open(input_path)
+    except FileNotFoundError:
+        return print("The Input File wasn't found. Check Path")
+
+    width, height = IMAGE.size
+
+    IMAGE = IMAGE.convert("L")
+    IMAGE = ImageOps.autocontrast(IMAGE, 10)
+
+    lines = []
+
+    if argument.draw_contours:
+        lines += get_contours(IMAGE.resize((argument.resolution // argument.contour_simplify,
+                                            argument.resolution // argument.contour_simplify * height // width)))
+
+    if argument.draw_hatch:
+        lines += hatch(IMAGE.resize(
+            (argument.resolution // argument.hatch_size, argument.resolution // argument.hatch_size * height // width)))
+
+    lines = sortlines(lines)
+
+    if argument.show_bitmap:
+        disp = Image.new("RGB", (argument.resolution, argument.resolution * height // width), (255, 255, 255))
+        draw = ImageDraw.Draw(disp)
+        for l in lines:
+            draw.line(l, (0, 0, 0), 5)
+        disp.show()
+
+    # if out_ext != '.svg':
+    #     now = datetime.now()
+    #     svg_path = output_path.rsplit('/', 1)[0] + now.strftime("%Y%m%d%H%M%S%f") + '.svg'
+    # else:
+    #     svg_path = output_path
+
+    file = open(output_path, 'w')
+    file.write(make_svg(lines))
+    file.close()
+
+    # if out_ext != '.svg':
+    #     if not is_image_file(output_path):
+    #         return "Output path is not an image path"
+    #     rasterise_image(svg_path,output_path)
+    #     os.remove(svg_path)
+    print(len(lines), "strokes.")
+    if argument.save_settings:
+        argument.save(os.path.dirname(output_path) + '/settings.json')
+    print("done.")
+    return lines
+
+
+def get_contours(image):
+    print("Generating Contours....")
+    image = find_edges(image)
+    image_copy1 = image.copy()
+    image_copy2 = image.rotate(-90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)
+    image_copy1_dots = get_dots(image_copy1)
+    image_copy1_contours = connect_dots(image_copy1_dots)
+    image_copy2_dots = get_dots(image_copy2)
+    image_copy2_contours = connect_dots(image_copy2_dots)
+
+    for i in range(len(image_copy2_contours)):
+        image_copy2_contours[1] = [(c[1], c[0]) for c in image_copy2_contours[i]]
+    contours = image_copy1_contours + image_copy2_contours
+
+    for i in range(len(contours)):
+        for j in range(len(contours)):
+            if len(contours[i]) > 0 and len(contours[j]) > 0:
+                if distsum(contours[j][0], contours[i][-1]) < 8:
+                    contours[i] = contours[i] + contours[j]
+                    contours[j] = []
+
+    for i in range(len(contours)):
+        contours[i] = [contours[i][j] for j in range(0, len(contours[i]), 8)]
+
+    contours = [c for c in contours if len(c) > 1]
+
+    for i in range(0, len(contours)):
+        contours[i] = [(v[0] * argument.contour_simplify, v[1] * argument.contour_simplify) for v in contours[i]]
+
+    for i in range(0, len(contours)):
+        for j in range(0, len(contours[i])):
+            contours[i][j] = int(contours[i][j][0] + 10 * perlin.noise(i * 0.5, j * 0.1, 1)), int(
+                contours[i][j][1] + 10 * perlin.noise(i * 0.5, j * 0.1, 2))
+
+    return contours
+
+
+def find_edges(image):
+    print("Fining Edges....")
+    if argument.no_cv:
+        appmask(image, [F_SobelX, F_SobelY])
+    else:
+        import numpy as np
+        import cv2
+        image = np.array(image)
+        image = cv2.GaussianBlur(image, (3, 3), 0)
+        image = cv2.Canny(image, 100, 200)
+        image = Image.fromarray(image)
+    return image.point(lambda p: p > 128 and 255)
+
+
+def get_dots(image):
+    print("Getting contour points...")
+    PX = image.load()
+    dots = []
+    width, height = image.size
+    for y in range(height - 1):
+        row = []
+        for x in range(1, width):
+            if PX[x, y] == 255:
+                if len(row) > 0:
+                    if x - row[-1][0] == row[-1][-1] + 1:
+                        row[-1] = (row[-1][0], row[-1][-1] + 1)
+                    else:
+                        row.append((x, 0))
+                else:
+                    row.append((x, 0))
+        dots.append(row)
+    return dots
+
+
+def connect_dots(dots):
+    print("Connecting contour points....")
+    contours = []
+    for y in range(len(dots)):
+        for x, v in dots[y]:
+            if v > -1:
+                if y == 0:
+                    contours.append([(x, y)])
+                else:
+                    closest = -1
+                    cdist = 100
+                    for x0, v0 in dots[y - 1]:
+                        if abs(x0 - x) < cdist:
+                            cdist = abs(x0 - x)
+                            closest = x0
+                    if cdist > 3:
+                        contours.append([(x, y)])
+                    else:
+                        found = 0
+                        for i in range(len(contours)):
+                            if contours[i][-1] == (closest, y - 1):
+                                contours[i].append((x, y,))
+                                found = 1
+                                break
+                        if found == 0:
+                            contours.append([(x, y)])
+        for c in contours:
+            if c[-1][1] < y - 1 and len(c) < 4:
+                contours.remove(c)
+    return contours
+
+
+def hatch(image):
+    print("Hatching....")
+    PX = image.load()
+    width, height = image.size
+    lg1 = []
+    lg2 = []
+    for x0 in range(width):
+        for y0 in range(height):
+            x = x0 * argument.hatch_size
+            y = y0 * argument.hatch_size
+            if PX[x0, y0] > 144:
+                pass
+            elif PX[x0, y0] > 64:
+                lg1.append([(x, y + argument.hatch_size / 4), (x + argument.hatch_size, y + argument.hatch_size / 4)])
+            elif PX[x0, y0] > 16:
+                lg1.append([(x, y + argument.hatch_size / 4), (x + argument.hatch_size, y + argument.hatch_size / 4)])
+                lg2.append([(x + argument.hatch_size, y), (x, y + argument.hatch_size)])
+            else:
+                lg1.append([(x, y + argument.hatch_size / 4), (x + argument.hatch_size, y + argument.hatch_size / 4)])
+                lg1.append([(x, y + argument.hatch_size / 2 + argument.hatch_size / 4),
+                            (x + argument.hatch_size, y + argument.hatch_size / 2 + argument.hatch_size / 4)])
+                lg2.append([(x + argument.hatch_size, y), (x, y + argument.hatch_size)])
+    lines = [lg1, lg2]
+    for k in range(0, len(lines)):
+        for i in range(0, len(lines[k])):
+            for j in range(0, len(lines[k])):
+                if lines[k][i] != [] and lines[k][j] != []:
+                    if lines[k][i][-1] == lines[k][j][0]:
+                        lines[k][i] = lines[k][i] + lines[k][j][1:]
+                        lines[k][j] = []
+        lines[k] = [l for l in lines[k] if len(l) > 0]
+    lines = lines[0] + lines[1]
+    for i in range(0, len(lines)):
+        for j in range(0, len(lines[i])):
+            lines[i][j] = int(lines[i][j][0] + argument.hatch_size * perlin.noise(i * 0.5, j * 0.1, 1)), int(
+                lines[i][j][1] + argument.hatch_size * perlin.noise(i * 0.5, j * 0.1, 2)) - j
+    return lines
+
+
+def make_svg(lines):
+    print("Generating SVG file....")
+    out = '<svg xmlns="http://www.w3.org/2000/svg" version="1.1">'
+    for l in lines:
+        l = ",".join([str(p[0] * 0.5) + "," + str(p[1] * 0.5) for p in l])
+        out += '<polyline points="' + l + '" stroke="black" stroke-width="2" fill="none" />\n'
+    out += '</svg>'
+    return out
+
+
+def rasterise_image(svg_image, raster_image):
+    print("Converting image....")
+    # to be implemented

strokesort.py → line_draw/strokesort.py

@@ -1,6 +1,6 @@
 from random import *
 from PIL import Image, ImageDraw, ImageOps
-from util import *
+from line_draw.util import *
 
 
 def sortlines(lines):
@@ -38,8 +38,8 @@ def visualize(lines):
     turtle.mainloop()
 
 if __name__=="__main__":
-    import linedraw
+    import line_draw
     #linedraw.draw_hatch = False
-    lines = linedraw.sketch("Lenna")
+    lines = line_draw.sketch("Lenna")
     #lines = sortlines(lines)
     visualize(lines)

line_draw/util.py

@@ -0,0 +1,22 @@
+import os
+def midpt(*args):
+    xs,ys = 0,0
+    for p in args:
+        xs += p[0]
+        ys += p[1]
+    return xs/len(args),ys/len(args)
+
+def distsum(*args):
+    return sum([ ((args[i][0]-args[i-1][0])**2 + (args[i][1]-args[i-1][1])**2)**0.5 for i in range(1,len(args))])
+
+
+def is_image_file(file_path):
+    image_extensions = ['.jpg', '.jpeg', '.png']
+    tmp,ext = extract_file_name_and_extension(file_path)
+    return ext in image_extensions
+
+
+def extract_file_name_and_extension(file_path):
+    file_name_with_extension = os.path.basename(file_path)
+    file_name, file_extension = os.path.splitext(file_name_with_extension)
+    return file_name, file_extension