rle tools

README.md

rle tools for converting a png to nouns rle encoding

NOTE: this is very rough and values are hard coded. publishing just for education. feel free to improve it.

first extract colors with colors.py next encode with encoder.py use decoder.py to view output

colors.py

from matplotlib import image
from colormap import rgb2hex
import numpy as np
import glob
import json
from collections import OrderedDict

f = open("./partcolors.json", "r")
meta = json.load(f)

colors = OrderedDict()
for c in meta["partcolors"]:
    colors[c] = True

for file in glob.glob("./imgs/*.png"):
    img = image.imread(file)
    a = np.where(img[:,:,3] != 0)
    bbox = np.min(a[0]), np.max(a[0]), np.min(a[1]), np.max(a[1])
    cropped = img[bbox[0]:bbox[1]+1, bbox[2]:bbox[3]+1]

    for y in cropped:
        for x in y:
            if x[3] != 0:
                c = rgb2hex(int(x[0]*255), int(x[1]*255), int(x[2]*255))
                colors[c[1:]] = True

meta["partcolors"] = list(colors.keys())

f = open("./partcolors.json", "w")
json.dump(meta, f, indent=4)

decoder.py

from eth_utils import to_bytes
import json
from matplotlib import pyplot as plt
import numpy as np
from colormap import hex2rgb

f = open("./encoded-layers.json", "r")
meta = json.load(f)

granularity = 64
resolution = 320

lookup = range(0, resolution, int(resolution/granularity))

img = np.zeros((350, 350, 4))
for parts in meta["parts"]:
    part = parts[0]
    subimg = to_bytes(hexstr=part["data"])
    top = subimg[1]
    right = subimg[2]
    bottom = subimg[3]
    left = subimg[4]

    print(top, right, bottom, left)

    x = left
    y = top

    for i in range(5, len(subimg), 2):
        length = subimg[i]
        c = meta["partcolors"][subimg[i+1]]
        if c != "":
            rgb = hex2rgb("#" + c)
            img[lookup[y] : lookup[y+1], lookup[x]: lookup[x] + lookup[length], :3] = np.array(rgb) / 255
            img[lookup[y] : lookup[y+1], lookup[x]: lookup[x] + lookup[length], 3] = 1.0

        print(x, length, right)
        x += length
        if x == right:
            x = left
            y += 1

plt.imshow(img)
plt.show()

encoder.py

from matplotlib import image
import numpy as np
from colormap import rgb2hex
import json
from eth_utils import to_hex

f = open("./partcolors.json", "r")
partcolors = json.load(f)

colors = {0:0}
for i, c in enumerate(partcolors["partcolors"]):
    colors[c] = i

img = image.imread("./imgs/police64x64_0009_face.png")

a = np.where(img[:,:,3] != 0)
bbox = np.min(a[0]), np.max(a[0]), np.min(a[1]), np.max(a[1])
cropped = img[bbox[0]:bbox[1]+1, bbox[2]:bbox[3]+1]

encoded = [0, bbox[0], bbox[3]+1, bbox[1]+1, bbox[2]]

for y in cropped:
    n = 0
    prev, cur = -1, -1
    out = ""
    for x in y:
        prev = cur

        if x[3] == 0:
            cur = 0
        else:
            # matplotlib reads in bgr
            cur = rgb2hex(int(x[0]*255), int(x[1]*255), int(x[2]*255))[1:]

        out += str(colors[cur])

        if cur != prev and prev != -1:
            encoded.append(n)
            encoded.append(colors[prev])
            n = 0

        n += 1

    encoded.append(n)
    encoded.append(colors[cur])
    print(out)
    out = ""

f = open("./output.json", "r")

print(len(encoded))
meta = json.load(f)
meta["parts"].append([{
    "name": "black-hoodie",
    "data": to_hex(bytes(encoded))
}])

f = open("./output.json", "w")
json.dump(meta, f, indent=4)