Spaces:
Running on Zero
Running on Zero
File size: 5,193 Bytes
834d1cf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 | from __future__ import annotations
import argparse
import sys
from pathlib import Path
if __package__ is None or __package__ == "":
sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
from mirrorppr.data.ffhq_wild_blend import (
FFHQ_SHIFT_DIRECTIONS,
FFHQWildFrameAugmentor,
blend_aligned_face_into_wild,
crop_aligned_from_quad,
load_wild_info,
)
from mirrorppr.data.image_ops import bgr_to_pil, load_rgb
from mirrorppr.data.io import read_json
from mirrorppr.data.llw_face_editor import LLWFaceRetoucher, normalize_operations
def parse_operation_specs(args: argparse.Namespace) -> list[dict[str, object]]:
specs = []
if args.operations:
specs.extend(item.strip() for item in args.operations.split(",") if item.strip())
if not specs:
raise ValueError("Provide --operations name:strength[,name:strength...].")
return normalize_operations(specs)
def resolve_wild_info(args: argparse.Namespace) -> dict[str, object]:
if args.wild_info_json:
data = read_json(args.wild_info_json)
if not isinstance(data, dict) or "face_quad" not in data:
raise ValueError("--wild-info-json must contain a JSON object with face_quad.")
return data
if args.ffhq_metadata and args.image_id:
return load_wild_info(args.ffhq_metadata, args.image_id)
raise ValueError("Provide crop information with --ffhq-metadata plus --image-id, or --wild-info-json.")
def save_wild_frame_augmentations(
source_wild,
target_wild,
wild_info: dict[str, object],
output_dir: Path,
count: int,
) -> int:
output_dir.mkdir(parents=True, exist_ok=True)
augmentor = FFHQWildFrameAugmentor(wild_info, wild_size=source_wild.size)
directions = list(FFHQ_SHIFT_DIRECTIONS.items())[:count]
for idx, (direction_name, direction_vec) in enumerate(directions):
shifted_quad = augmentor.get_shifted_quad(direction_vec, magnitude_ratio=1.0)
source_out = output_dir / f"simulated_{idx:03d}_{direction_name}_source.png"
target_out = output_dir / f"simulated_{idx:03d}_{direction_name}_target.png"
crop_aligned_from_quad(source_wild, shifted_quad).save(source_out)
crop_aligned_from_quad(target_wild, shifted_quad).save(target_out)
return len(directions)
def run_single(args: argparse.Namespace) -> None:
output_dir = Path(args.output_dir)
output_dir.mkdir(parents=True, exist_ok=True)
stale_manifest = output_dir / "manifest.json"
if stale_manifest.exists() or stale_manifest.is_symlink():
stale_manifest.unlink()
if args.num_augmentations > 0 and not args.wild_image:
raise ValueError("Faithful simulated self-augmentation requires --wild-image and crop information. Use --num-augmentations 0 to only save the aligned pair.")
operations = parse_operation_specs(args)
retoucher = LLWFaceRetoucher()
edited_bgr = retoucher.apply_operations(args.aligned_image, operations)
edited_aligned = bgr_to_pil(edited_bgr)
aligned = load_rgb(args.aligned_image)
aligned_source_out = output_dir / "aligned_source.png"
aligned_target_out = output_dir / "aligned_target.png"
aligned.save(aligned_source_out)
edited_aligned.save(aligned_target_out)
if args.wild_image:
wild = load_rgb(args.wild_image)
wild_info = resolve_wild_info(args)
face_quad = wild_info["face_quad"]
wild_source = blend_aligned_face_into_wild(aligned, wild, face_quad)
wild_source_out = output_dir / "wild_source.png"
wild_source.save(wild_source_out)
wild_retouched = blend_aligned_face_into_wild(edited_aligned, wild, face_quad)
wild_target_out = output_dir / "wild_target.png"
wild_retouched.save(wild_target_out)
if args.num_augmentations > 0:
save_wild_frame_augmentations(
wild_source,
wild_retouched,
wild_info,
output_dir / "augmentations",
min(args.num_augmentations, len(FFHQ_SHIFT_DIRECTIONS)),
)
elif args.num_augmentations > 0:
raise ValueError("Internal error: wild inputs are required before saving simulated augmentations.")
def build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description="Construct MirrorPPR simulated subset samples.")
parser.add_argument("--aligned-image", required=True, help="1024x1024 aligned FFHQ image.")
parser.add_argument(
"--operations",
default=None,
help="Comma-separated operations as name:strength, e.g. eye_resize:100,nose_alar:-100.",
)
parser.add_argument("--output-dir", required=True)
parser.add_argument("--wild-image", default=None)
parser.add_argument("--ffhq-metadata", default=None)
parser.add_argument("--image-id", default=None)
parser.add_argument("--wild-info-json", default=None, help="JSON file with face_quad and optional face_rect/pixel_size.")
parser.add_argument("--num-augmentations", type=int, default=8)
return parser
def main() -> None:
args = build_parser().parse_args()
run_single(args)
if __name__ == "__main__":
main()
|