Setting a list of (x,y) cooordinates into an array so polygons are drawn

Question:

I have some code that prints out a list of coordinates (stored in points

f=open('139cm_2000_frame27.json') 
data=json.load(f) 
shapes=data["shapes"] 
for i in shapes: 
    print(i['label'])   # prints the label first
    for c in i['points']:
        d=np.array(c)
        print(d)       # an array containing coordinates in the form (x,y) 

d, the coordinates, are the points of n number of 10 sided polygons. So coordinates 0-9 are the coordinates of the first polygon, coordinates 10-19 are the second polygon…

There could be any number of polygons in the json file but they will each, always, have 10 coordinates.

I need to find a way of using those coordinates to ‘draw’/’recreate’ these polygons in a 128×128 array.

I have tried

from skimage.draw import polygon
   img = np.zeros((128, 128), dtype=np.uint8)
   r = np.array([#the x coordinates of d])
   c = np.array([#the y coordinates of d])
   rr, cc = polygon(r, c)
   img[rr, cc] = 1 #unsure about the 1
   img

but I do not know how to 1) get sets of 10 coordinates and 2) read the xs into r and the ys into c

Thank you so much!

An example of the input json:

{
  "version": "4.6.0",
  "flags": {},
  "shapes": [
    {
      "label": "blob",
      "points": [
        [
          61.42857142857143,
          20.285714285714285
        ],
        [
          59.10047478151446,
          18.879430437885873
        ],
        [
          58.04359793578868,
          16.37330203102605
        ],
        [
          58.661631924538575,
          13.724584936383643
        ],
        [
          60.71850877026435,
          11.94499905752918
        ],
        [
          63.42857142857143,
          11.714285714285715
        ],
        [
          65.75666807562841,
          13.120569562114127
        ],
        [
          66.81354492135418,
          15.62669796897395
        ],
        [
          66.19551093260428,
          18.275415063616357
        ],
        [
          64.13863408687851,
          20.05500094247082
        ]
      ],
      "group_id": null,
      "shape_type": "polygon",
      "flags": {}
    },
    {
      "label": "blob",
      "points": [
        [
          88.71428571428572,
          82.42857142857143
        ],
        [
          85.63470409582908,
          81.33512050565437
......
Asked By: Joseph Darton

||

Answers:

From software engineering point of view, it is recomended to break your code into simple separate parts (i.e. make it modular).

First you will need a function for reading the input json and parsing it. I called it read_input in the code below.
The format of the parsed data depends on the application.
I chose to return a list of pairs of ndarrays. Each element in the list represents one polygon. Each polygon contains 2 ndarrays: 1 for the x coordinates, and 1 for the y coordinates. I chose this representation because it is convenient for drawing the polygons (see below).

Second you will need a function for drawing the polygons (draw_polygons). It will contain an iteration over the polygon list, and call a lower level function for drawing 1 polygon (draw_one_polygon), again for modular reasons.

See the code below:

import json
import numpy as np
from skimage.draw import polygon

def read_input(filename: str):
    polygons = []
    with open(filename) as f:
        data = json.load(f)
        shapes = data["shapes"]
        for i in shapes:
            cur_poly_points = i["points"]
            tmp = list(zip(*cur_poly_points))
            # NOTE: The following line assumes that the point coordinates are given as (x,y). 
            #       Change the order of the indices if needed.
            polygons.append((np.array(tmp[1]), np.array(tmp[0])))
    return polygons

def draw_one_polygon(img, one_poly):
    r = one_poly[0];
    c = one_poly[1];
    rr, cc = polygon(r, c)
    img[rr,cc] = 1

def draw_polygons(img, polygons):
    for poly in polygons:
        draw_one_polygon(img, poly)

filename = '139cm_2000_frame27.json'
polygons = read_input(filename)
img = np.zeros((128, 128), dtype=np.uint8)
draw_polygons(img, polygons)
print(img)

Note: in your actual code you should verify that the coordinates do not exceed the image dimension.

Documentation and example: skimage.draw.polygon

If you are not familiar with this notation: *cur_poly_points, see here: How to unzip a list of tuples into individual lists?.

Answered By: wohlstad