현재 작업 상태 저장
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Yun Chan
parent
07cc67761e
commit
6bd91b0d5e
674 changed files with 8726 additions and 298 deletions
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#!/usr/bin/env python3
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"""Turn an imagegen eye atlas into coordinate-locked app eye parts."""
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from __future__ import annotations
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import json
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import shutil
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from pathlib import Path
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import cv2
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import numpy as np
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from PIL import Image, ImageDraw
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HERE = Path(__file__).resolve().parent
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REPO_ROOT = HERE.parents[3]
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ATLAS = HERE / "imagegen" / "eye-expression-atlas-v1.png"
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OUT = HERE / "imagegen" / "eye-variants"
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PARTS = OUT / "parts"
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APP_PARTS = REPO_ROOT / "apps/web/public/avatar/seoyeon-live2d-psb/parts"
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CANVAS = (900, 1125)
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TARGETS = {
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"joy": {
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"brow-left": (308, 292, 436, 317),
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"brow-right": (472, 283, 601, 300),
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"eye-left": (296, 312, 436, 365),
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"eye-right": (472, 303, 619, 356),
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},
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"sad": {
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"brow-left": (308, 294, 436, 322),
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"brow-right": (472, 286, 601, 308),
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"eye-left": (296, 306, 436, 392),
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"eye-right": (472, 297, 619, 377),
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},
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"startled": {
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"brow-left": (308, 286, 436, 313),
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"brow-right": (472, 277, 601, 300),
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"eye-left": (296, 292, 436, 392),
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"eye-right": (472, 283, 619, 377),
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},
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}
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ROW_NAMES = ["joy", "sad", "startled"]
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ROW_PARTS = ["brow-left", "brow-right", "eye-left", "eye-right"]
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def alpha_bbox(im: Image.Image, threshold: int = 8) -> tuple[int, int, int, int] | None:
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alpha = np.array(im.convert("RGBA").getchannel("A"))
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ys, xs = np.where(alpha > threshold)
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if len(xs) == 0:
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return None
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return int(xs.min()), int(ys.min()), int(xs.max() + 1), int(ys.max() + 1)
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def chroma_to_alpha(im: Image.Image) -> Image.Image:
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arr_u8 = np.array(im.convert("RGBA"))
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rgb_u8 = arr_u8[:, :, :3]
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hsv = cv2.cvtColor(rgb_u8, cv2.COLOR_RGB2HSV)
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hue = hsv[:, :, 0]
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sat = hsv[:, :, 1]
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val = hsv[:, :, 2]
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green_bg = (hue >= 42) & (hue <= 92) & (sat > 45) & (val > 18)
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# Keep a tiny soft edge by making only clearly non-green pixels opaque.
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alpha = np.where(green_bg, 0, 255).astype(np.uint8)
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alpha = cv2.medianBlur(alpha, 3)
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arr = arr_u8.astype(np.float32)
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rgb = arr[:, :, :3]
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greenish_edge = (rgb[:, :, 1] > rgb[:, :, 0] + 8) & (rgb[:, :, 1] > rgb[:, :, 2] + 8)
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rgb[:, :, 1] = np.where(greenish_edge, np.minimum(rgb[:, :, 1], np.maximum(rgb[:, :, 0], rgb[:, :, 2]) + 12), rgb[:, :, 1])
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arr[:, :, :3] = rgb
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arr[:, :, 3] = alpha
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arr[arr[:, :, 3] < 2, :3] = 0
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return Image.fromarray(np.clip(arr, 0, 255).astype(np.uint8), "RGBA")
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def component_boxes(alpha_im: Image.Image) -> list[tuple[int, int, int, int]]:
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alpha = np.array(alpha_im.getchannel("A"))
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mask = (alpha > 22).astype(np.uint8)
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num, _labels, stats, _centroids = cv2.connectedComponentsWithStats(mask, 8)
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boxes: list[tuple[int, int, int, int, int]] = []
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for i in range(1, num):
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x, y, w, h, area = stats[i]
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if area > 200:
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boxes.append((int(x), int(y), int(x + w), int(y + h), int(area)))
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boxes.sort(key=lambda box: (box[1], box[0]))
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if len(boxes) != 12:
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raise RuntimeError(f"Expected 12 eye atlas components, got {len(boxes)}: {boxes}")
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return [(x0, y0, x1, y1) for x0, y0, x1, y1, _area in boxes]
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def crop_with_padding(im: Image.Image, box: tuple[int, int, int, int], padding: int = 10) -> Image.Image:
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x0, y0, x1, y1 = box
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x0 = max(0, x0 - padding)
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y0 = max(0, y0 - padding)
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x1 = min(im.width, x1 + padding)
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y1 = min(im.height, y1 + padding)
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return im.crop((x0, y0, x1, y1))
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def fit_into_canvas(crop: Image.Image, target: tuple[int, int, int, int]) -> Image.Image:
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target_w = target[2] - target[0]
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target_h = target[3] - target[1]
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box = alpha_bbox(crop)
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source = crop.crop(box) if box else crop
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scale = min(target_w / source.width, target_h / source.height)
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size = (max(1, round(source.width * scale)), max(1, round(source.height * scale)))
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source = source.resize(size, Image.Resampling.LANCZOS)
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canvas = Image.new("RGBA", CANVAS, (0, 0, 0, 0))
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x = target[0] + (target_w - source.width) // 2
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y = target[1] + (target_h - source.height) // 2
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canvas.alpha_composite(source, (x, y))
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return canvas
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def make_contact(entries: list[dict[str, object]]) -> None:
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tile_w, tile_h = 180, 150
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cols = 4
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rows = 3
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sheet = Image.new("RGBA", (tile_w * cols, tile_h * rows), (30, 39, 36, 255))
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draw = ImageDraw.Draw(sheet)
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for i, entry in enumerate(entries):
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part = Image.open(PARTS / str(entry["file"])).convert("RGBA")
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box = alpha_bbox(part)
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thumb = part.crop(box) if box else part
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thumb.thumbnail((tile_w - 24, tile_h - 42), Image.Resampling.LANCZOS)
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x = (i % cols) * tile_w + (tile_w - thumb.width) // 2
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y = (i // cols) * tile_h + 10
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sheet.alpha_composite(thumb, (x, y))
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draw.text(((i % cols) * tile_w + 8, (i // cols) * tile_h + tile_h - 30), str(entry["id"]), fill=(220, 228, 224, 255))
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draw.text(((i % cols) * tile_w + 8, (i // cols) * tile_h + tile_h - 15), str(entry["alphaBox"]), fill=(150, 166, 160, 255))
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sheet.save(OUT / "eye-variants-contact.png", optimize=True)
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def sync_to_app() -> None:
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APP_PARTS.mkdir(parents=True, exist_ok=True)
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for source in PARTS.glob("*.png"):
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shutil.copy2(source, APP_PARTS / source.name)
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def main() -> int:
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if not ATLAS.exists():
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raise FileNotFoundError(ATLAS)
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OUT.mkdir(parents=True, exist_ok=True)
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PARTS.mkdir(parents=True, exist_ok=True)
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keyed = chroma_to_alpha(Image.open(ATLAS))
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keyed.save(OUT / "eye-expression-atlas-alpha.png", optimize=True)
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boxes = component_boxes(keyed)
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entries: list[dict[str, object]] = []
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for row_index, variant in enumerate(ROW_NAMES):
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row_boxes = boxes[row_index * 4 : row_index * 4 + 4]
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for part_name, source_box in zip(ROW_PARTS, row_boxes):
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part_id = f"eyegen-{variant}-{part_name}"
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crop = crop_with_padding(keyed, source_box)
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canvas = fit_into_canvas(crop, TARGETS[variant][part_name])
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path = PARTS / f"{part_id}.png"
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canvas.save(path, optimize=True)
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box = alpha_bbox(canvas)
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entries.append(
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{
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"id": part_id,
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"file": path.name,
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"sourceBox": list(source_box),
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"targetBox": list(TARGETS[variant][part_name]),
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"alphaBox": list(box) if box else None,
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}
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)
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(OUT / "eye-variants-manifest.json").write_text(
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json.dumps(
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{
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"source": str(ATLAS),
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"canvas": CANVAS,
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"variants": ROW_NAMES,
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"parts": entries,
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},
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ensure_ascii=False,
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indent=2,
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),
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encoding="utf-8",
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)
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make_contact(entries)
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sync_to_app()
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print(f"extracted {len(entries)} imagegen eye variant parts")
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print(f"parts {PARTS}")
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print(f"app parts {APP_PARTS}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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