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from PIL import Image, ImageOps
import numpy as np
from create_print_layover import create_hard_light_layover
import cv2
def create_layover(background_image, layer_image, opacity):
background_img_raw = Image.open(background_image)
background_img_raw = background_img_raw.convert("RGBA")
background_img = np.array(background_img_raw)
background_img_float = background_img.astype(float)
foreground_img_raw = Image.open(layer_image)
foreground_img_raw = foreground_img_raw.convert("RGBA")
foreground_img = np.array(foreground_img_raw)
foreground_img_float = foreground_img.astype(float)
blended_img_float = create_hard_light_layover(background_img_float, foreground_img_float, opacity)
blended_img = np.uint8(blended_img_float)
blended_img_raw = Image.fromarray(blended_img)
output_path = "lay_over_image.png"
blended_img_raw.save(output_path)
return output_path
def create_image_tile(input_patch, x_dim, y_dim):
input_image = Image.open(input_patch)
input_image = input_image.convert("RGB")
width, height = input_image.size
output_image = Image.new("RGB", (x_dim, y_dim))
for y in range(0, y_dim, height):
for x in range(0, x_dim, width):
region_height = min(height, y_dim - y)
region_width = min(width, x_dim - x)
region = input_image.crop((0, 0, region_width, region_height))
output_image.paste(region, (x, y))
output_image.save('tiled_image.png')
def create_image_cutout(texture_transfer_image, actual_mask):
image = Image.open(texture_transfer_image).convert('RGB')
mask = Image.open(actual_mask).convert('L')
if mask.size != image.size:
image = image.resize(mask.size, Image.Resampling.NEAREST)
image_np = np.array(image)
mask_np = np.array(mask)
binary_mask = (mask_np > 127).astype(np.uint8)
masked_image_np = image_np * np.expand_dims(binary_mask, axis=-1)
masked_image = Image.fromarray(masked_image_np.astype(np.uint8))
masked_image.save('cut_out_image.png')
def paste_image(base_image_path, cutout_image_path, mask_path):
background = Image.open(base_image_path).convert("RGB")
cutout = Image.open(cutout_image_path)
mask = Image.open(mask_path).convert("L")
if cutout.mode == 'RGBA':
cutout_rgb = cutout.convert("RGB")
cutout_alpha = cutout.split()[-1]
else:
cutout_rgb = cutout.convert("RGB")
cutout_alpha = mask
cutout_rgb = cutout_rgb.resize(background.size, Image.Resampling.NEAREST)
cutout_alpha = cutout_alpha.resize(background.size, Image.Resampling.NEAREST)
cutout_rgb_np = np.array(cutout_rgb)
background_np = np.array(background)
cutout_alpha_np = np.array(cutout_alpha)
cutout_alpha_np = cutout_alpha_np / 255.0
cutout_masked = (cutout_rgb_np * cutout_alpha_np[..., np.newaxis]).astype(np.uint8)
background_masked = (background_np * (1 - cutout_alpha_np[..., np.newaxis])).astype(np.uint8)
result_np = cutout_masked + background_masked
result = Image.fromarray(result_np)
result.save('result.png')
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