Files
2025-11-28 16:00:46 +01:00

115 lines
3.8 KiB
Python

from PIL import Image, ImageFilter, ImageDraw
from dataclasses import dataclass
from functools import cached_property
from pathlib import Path
import numpy as np
from .patch_detector import PatchDetector
from .editor_ctx import EditorCtx
@dataclass
class PatchMerger:
"""
Merges two images based on a detected patch, with various processing options.
This class takes the heatmap from the PatchDetector and processes it to create
a final mask. This mask is then used to composite the edited image onto the
original image. It also provides methods for saving the merged image and
debug artifacts.
"""
detector: PatchDetector
@cached_property
def ctx(self) -> EditorCtx:
return self.detector.ctx
@cached_property
def raw_mask(self) -> Image.Image:
heatmap = self.detector.heatmap
threshold = self.detector.detection_alg.get_threshold(self.ctx.tolerance)
# Apply threshold
mask = heatmap.point(lambda p: 255 if p > threshold else 0)
# Drop smaller areas
if self.ctx.min_area_size > 1:
# Filter size must be odd
filter_size = self.ctx.min_area_size | 1
# Erode then Dilate (Opening) to remove small noise
mask = mask.filter(ImageFilter.MinFilter(filter_size))
mask = mask.filter(ImageFilter.MaxFilter(filter_size))
return mask
@cached_property
def sized_mask(self) -> Image.Image:
mask = self.raw_mask
if self.ctx.mask_expansion == 0:
return mask
# The kernel size for a radius of N is 2*N+1
size = abs(self.ctx.mask_expansion) * 2 + 1
if self.ctx.mask_expansion > 0:
# Expand (Dilation)
return mask.filter(ImageFilter.MaxFilter(size))
else:
# Shrink (Erosion)
return mask.filter(ImageFilter.MinFilter(size))
@cached_property
def final_mask(self) -> Image.Image:
mask = self.sized_mask
if self.ctx.blur_radius > 0:
mask = mask.filter(ImageFilter.GaussianBlur(self.ctx.blur_radius))
return mask
@cached_property
def merged_image(self) -> Image.Image:
img_orig, img_edit = self.detector.images
mask = self.final_mask
if self.ctx.edit_max_alpha < 1.0:
img_edit = Image.blend(img_orig, img_edit, self.ctx.edit_max_alpha)
# The `img_edit` is already warped and pasted on a copy of the original.
# We use composite to merge the images using the final mask.
merged = Image.composite(img_edit, img_orig, mask)
return merged.convert("RGBA")
@cached_property
def debug_overlay(self) -> Image.Image:
# Overlay
img1 = self.detector.images[0]
overlay = img1.copy().convert('RGBA')
# Create a red highlight layer
highlight = Image.new('RGBA', overlay.size, (255, 0, 0, 128))
# Blend highlight over overlay
blended = Image.alpha_composite(overlay, highlight)
# Composite using mask
return Image.composite(blended, overlay, self.sized_mask)
@property
def base_name(self) -> str:
if self.ctx.original_img_path:
return self.ctx.original_img_path.stem
return "patch_result"
def save_merged(self, path: Path) -> None:
self.merged_image.save(path, qmin=0, qmax=0)
def save_debug(self, output_dir: Path) -> None:
output_dir.mkdir(parents=True, exist_ok=True)
self.detector.heatmap.save(output_dir / f"{self.base_name}-heatmap.png")
self.raw_mask.save(output_dir / f"{self.base_name}-raw_mask.png")
self.final_mask.save(output_dir / f"{self.base_name}-final_mask.png")
self.debug_overlay.save(output_dir / f"{self.base_name}-overlay.png")
self.detector.images[1].save(output_dir / f"{self.base_name}-wrapped.png")