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@loon3
Created March 7, 2023 18:31
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twelvefold-python
from PIL import Image
import random
# Load the input image and convert it to RGBA mode
input_image = Image.open("input_image.png").convert("RGBA")
# Calculate the size of each grid cell based on the input image size
cell_width = 200
cell_height = 200
# Calculate the size of the output image based on the grid cell size
output_width = 12 * cell_width
output_height = 12 * cell_height
# Create a new image with an alpha channel
output_image = Image.new("RGBA", (output_width, output_height), color=(0, 0, 0, 0))
# Loop over each cell in the grid
for x in range(12):
for y in range(12):
# Calculate the coordinates of the top-left corner of the cell
cell_x = x * cell_width
cell_y = y * cell_height
# Choose a random resize ratio from 0.1 to 1
resize_ratio = random.uniform(0.1, 1.2)
# Resize the input image using the Lanczos resampling filter
resized_input_image = input_image.resize(
(int(cell_width * resize_ratio), int(cell_height * resize_ratio)),
resample=Image.LANCZOS,
)
# Convert the resized input image to RGBA mode
resized_input_image = resized_input_image.convert("RGBA")
# Calculate the center coordinates of the cell
center_x = cell_x + cell_width // 2
center_y = cell_y + cell_height // 2
# Calculate the top-left coordinates of the resized input image
resized_x = center_x - resized_input_image.width // 2
resized_y = center_y - resized_input_image.height // 2
# Paste the resized input image into the output image, preserving transparency
output_image.alpha_composite(resized_input_image, (resized_x, resized_y))
# Save the output image
output_image.save("output_image.png")
from PIL import Image
import random
import math
# Load the input image and convert it to RGBA mode
input_image = Image.open("input_image.png").convert("RGBA")
# Calculate the size of each grid cell based on the input image size
cell_width = 200
cell_height = 200
# Calculate the size of the output image based on the grid cell size
output_width = 12 * cell_width
output_height = 12 * cell_height
# Create a new image with an alpha channel
output_image = Image.new("RGBA", (output_width, output_height), color=(0, 0, 0, 0))
angle = random.uniform(0, math.pi)
cos_angle = math.cos(angle)
sin_angle = math.sin(angle)
for x in range(12):
for y in range(12):
# Calculate the coordinates of the top-left corner of the cell
cell_x = x * cell_width
cell_y = y * cell_height
# Calculate the resize ratio based on two intersecting sine wave functions
ratio = (math.sin((x / 12) * math.pi * 2 + (y / 12) * math.pi * 4) + math.sin((cos_angle * x / 12 + sin_angle * y / 12) * math.pi * 2)) * 0.2 + 0.8
# Resize the input image using the Lanczos resampling filter
resized_input_image = input_image.resize(
(int(cell_width * ratio), int(cell_height * ratio)),
resample=Image.LANCZOS,
)
# Convert the resized input image to RGBA mode
resized_input_image = resized_input_image.convert("RGBA")
# Calculate the center coordinates of the cell
center_x = cell_x + cell_width // 2
center_y = cell_y + cell_height // 2
# Calculate the top-left coordinates of the resized input image
resized_x = center_x - resized_input_image.width // 2
resized_y = center_y - resized_input_image.height // 2
# Paste the resized input image into the output image, preserving transparency
output_image.alpha_composite(resized_input_image, (resized_x, resized_y))
# Save the output image
output_image.save("output_image.png")
@benchadwick
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output_image

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