atlas/tools/scale_back.py
AnonymousRandomPerson 224b22bba0 Updated Reddit
2024-01-01 16:09:57 -06:00

222 lines
5.5 KiB
Python

#!/usr/bin/python
from io import TextIOWrapper
import json
import traceback
import numpy
from PIL import Image, ImageDraw
import gc
import tqdm
"""
# 166 to 164 with reference of 165
shrink
166
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20
web\_img\canvas\place30\159.png
web\_img\canvas\place30\163_159.png
# 166 to 165 with reference of 166
shrink
166
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20
web\_img\canvas\place30\159.png
web\_img\canvas\place30\164_159.png
# 164 to 165 with reference of 165
shrink
164
165
20
web\_img\canvas\place30\159.png
web\_img\canvas\place30\163_159.png
# 166 to 167 with reference of 167
expand
166
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20
web\_img\canvas\place30\159.png
web\_img\canvas\place30\165_159.png
"""
class ScaleConfig:
type = 'expand'
source = ''
destination = ''
threshold = 20
image1 = ''
image2 = ''
def swap_source_dest(source, destination, image2):
ScaleConfig.source = source
ScaleConfig.destination = destination
ScaleConfig.image2 = image2
def remove_white(entry: dict):
canvas_ref = Image.new('RGBA', (2000,2000))
with Image.open(ScaleConfig.image1).convert('RGBA') as image1:
if ScaleConfig.image2:
with Image.open(ScaleConfig.image2).convert('RGBA') as image2:
canvas_ref.paste(image1, (0, 0), image1)
canvas_ref.paste(image2, (0, 0), image2)
else:
canvas_ref.paste(image1, (0, 0), image1)
# uncomment when you need to see the source canvas
# canvas_ref.show()
# print(entry['path'])
for (period, polygonList) in entry['path'].items():
# Check if the entry's period applies to the current scale config.
period_split = period.split(', ')
period_index = None
for i, period_section in enumerate(period_split):
if f'-{ScaleConfig.source}' in period_section or period_section == ScaleConfig.source:
period_index = i
break
if period_index is None:
continue
# Get bounding rectangle and have a list of tuples for polygon
polygon = []
x_box = 2000
y_box = 2000
x_box2 = 0
y_box2 = 0
for point in polygonList:
x_box = min(x_box, max(point[0] - 1.5, 0))
y_box = min(y_box, max(point[1] - 1.5, 0))
x_box2 = max(x_box2, min(point[0] + 1.5, 2000))
y_box2 = max(y_box2, min(point[1] + 1.5, 2000))
polygon.append(tuple(point))
x_box = int(x_box)
y_box = int(y_box)
x_box2 = int(x_box2)
y_box2 = int(y_box2)
# Crop the image based on polygon
# https://stackoverflow.com/questions/22588074/
imArray = numpy.asarray(canvas_ref)
with Image.new('L', (imArray.shape[1], imArray.shape[0]), 0) as maskIm:
ImageDraw.Draw(maskIm).polygon(polygon, outline=1, fill=1)
mask = numpy.array(maskIm)
newImArray = numpy.empty(imArray.shape,dtype='uint8')
newImArray[:,:,:3] = imArray[:,:,:3]
newImArray[:,:,3] = mask*255
imArray = newImArray[y_box:y_box2,x_box:x_box2,:]
# points = numpy.array([polygon])
# print(points)
# print(cv2.boundingRect(points[0]))
# print(1)
# print(imArray)
colored_pixel_count: int = 0
all_pixel_count: int = 0
# Read the area based on bounding box
for x in imArray:
for pixel in x:
if pixel[3] == 0: continue
all_pixel_count += 1
if (pixel[0] == 255 and pixel[1] == 255 and pixel[2] == 255): continue
colored_pixel_count += 1
if all_pixel_count == 0: break
colorness = (100 * colored_pixel_count)/all_pixel_count
if (ScaleConfig.type == "shrink" and colorness < ScaleConfig.threshold) or (ScaleConfig.type == "expand" and colorness > ScaleConfig.threshold):
print(f"[{entry['id']} {period}] {colored_pixel_count}/{all_pixel_count} ({colorness}%)")
if f'-{ScaleConfig.source}' in period:
period_section = period_section.replace(f'-{ScaleConfig.source}', f'-{ScaleConfig.destination}')
else:
period_section = f'{period_section}-{ScaleConfig.destination}'
period_split[period_index] = period_section
new_period = ', '.join(period_split)
entry['path'][new_period] = entry['path'][period]
del entry['path'][period]
entry['center'][new_period] = entry['center'][period]
del entry['center'][period]
break
# newIm = Image.fromarray(newImArray, "RGBA")
# newIm.show()
break
return entry
def per_line_entries(entries: list, file: TextIOWrapper):
"""
Returns a string of all the entries, with every entry in one line.
"""
file.write("[\n")
line_temp = ""
for entry in tqdm.tqdm(entries):
if line_temp:
file.write(line_temp + ",\n")
line_temp = json.dumps(entry, ensure_ascii=False)
file.write(line_temp + "\n]")
def format_all(entry: dict, silent=False):
def print_(*args, **kwargs):
if not silent:
print(*args, **kwargs)
entry = remove_white(entry)
print_("Completed!")
return entry
def scale_back_entries(entries):
for i in tqdm.trange(len(entries)):
try:
entry_formatted = format_all(entries[i], True)
entries[i] = entry_formatted
except Exception:
print(f"Exception occured when formatting ID {entries[i]['id']}")
print(traceback.format_exc())
if not (i % 50):
print(f"{i} checked.")
gc.collect()
def go(path):
print(f"Scaling whiteout for {path}...")
with open(path, "r+", encoding='UTF-8') as f1:
entries = json.loads(f1.read())
scale_back_entries(entries)
print(f"{len(entries)} checked. Writing...")
with open(path, "w", encoding='utf-8', newline='\n') as f2:
per_line_entries(entries, f2)
print("Writing completed. All done.")
if __name__ == '__main__':
ScaleConfig.type = input("Type (shrink/expand): ")
ScaleConfig.source = input("Source: ")
ScaleConfig.destination = input("Destination: ")
ScaleConfig.threshold = int(input("Threshold (%): "))
ScaleConfig.image1 = input("Reference canvas layer 1: ")
ScaleConfig.image2 = input("Reference canvas layer 2: ")
go("web/atlas.json")