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Running on Zero
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5c331a4 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 | """Headless learned-rig retargeting, rendered evidence and full-frame collision review."""
import json
import os
from pathlib import Path
import shutil
import subprocess
ROOT = Path(__file__).resolve().parents[1]
def _run(command, log_path, timeout=1800):
with Path(log_path).open("w") as log:
result = subprocess.run(command, stdout=log, stderr=subprocess.STDOUT, timeout=timeout)
if result.returncode:
tail = Path(log_path).read_text(errors="replace")[-4000:]
raise RuntimeError(f"Animation stage failed ({result.returncode}): {tail}")
def animate_character(
rigged_glb, motion_npz, motion_bvh, output_dir, *, body_clearance=True, smooth_joints=False
):
"""Retarget real Kimodo motion to a learned Mixamo rig; never substitutes a canned clip."""
import numpy as np
out = Path(output_dir).resolve()
out.mkdir(parents=True, exist_ok=True)
blender = os.getenv("BLENDER_BIN") or shutil.which("blender")
if not blender and Path("/Applications/Blender.app/Contents/MacOS/Blender").exists():
blender = "/Applications/Blender.app/Contents/MacOS/Blender"
if not blender:
raise RuntimeError("Blender is required for animation export and collision auditing.")
ffmpeg = shutil.which("ffmpeg")
if not ffmpeg:
raise RuntimeError("ffmpeg is required for the downloadable animation video.")
with np.load(motion_npz, allow_pickle=False) as motion:
poses = motion["posed_joints"]
if poses.ndim != 3 or poses.shape[2] != 3 or len(poses) < 2 or not np.isfinite(poses).all():
raise ValueError("Kimodo output must contain finite frame/joint/xyz motion.")
frames = len(poses)
def blender_stage(script, arguments, name, timeout=1800):
_run(
[
blender,
"--background",
"--python-exit-code",
"1",
"--python",
str(ROOT / "scripts" / script),
"--",
*map(str, arguments),
],
out / f"{name}.log",
timeout,
)
def retarget(destination, smooth, name):
destination.mkdir(parents=True, exist_ok=True)
blender_stage(
"retarget_character.py",
[
"--input",
Path(rigged_glb).resolve(),
"--motion",
Path(motion_npz).resolve(),
"--bvh",
Path(motion_bvh).resolve(),
"--output",
destination,
*(["--body-clearance"] if body_clearance else []),
*(["--smooth-joints", "--arm-blend-band", "0.9"] if smooth else []),
],
name,
)
blender_stage(
"audit_character_collisions.py",
["--input", destination / "animation.glb", "--output", destination / "audit", "--frames", frames],
name + "-audit",
3600,
)
audit = json.loads((destination / "audit" / "audit.json").read_text())
technical_animation_check(audit, frames)
(destination / "audit" / "audit.json").write_text(json.dumps(audit, indent=2))
return audit
selected = out
audit = retarget(out, smooth_joints, "retarget")
selection = {"selected": "baseline", "baseline": audit["summary"]}
if not audit["summary"]["technical_pass"] and not smooth_joints:
candidate_dir = out / "repairs" / "smooth-joints"
candidate = retarget(candidate_dir, True, "smooth-joints")
improved, comparison = repair_improves(audit, candidate, frames)
selection.update(candidate=candidate["summary"], comparison=comparison)
if improved:
selected, audit = candidate_dir, candidate
selection["selected"] = "smooth-joints"
(out / "repair-selection.json").write_text(json.dumps(selection, indent=2))
glb = selected / "animation.glb"
blender_stage(
"render_animation.py",
[
"--input",
glb,
"--output",
out / "frames",
"--step",
1,
"--size",
512,
"--angle",
"front",
"--frame-count",
frames,
],
"render",
3600,
)
video = out / "animation.mp4"
_run(
[
ffmpeg,
"-y",
"-framerate",
"30",
"-i",
str(out / "frames" / "%04d.png"),
"-c:v",
"libx264",
"-pix_fmt",
"yuv420p",
"-movflags",
"+faststart",
str(video),
],
out / "video.log",
)
from PIL import Image, ImageOps, ImageDraw
samples = sorted(set(round(i * (frames - 1) / 15) + 1 for i in range(16)))
sheet = Image.new("RGB", (4 * 256, 4 * 280), "#182830")
draw = ImageDraw.Draw(sheet)
for index, frame in enumerate(samples):
with Image.open(out / "frames" / f"{frame:04d}.png") as image:
sheet.paste(ImageOps.contain(image, (256, 256)), ((index % 4) * 256, (index // 4) * 280))
draw.text(((index % 4) * 256 + 8, (index // 4) * 280 + 258), f"Frame {frame}", fill="white")
sheet.save(out / "contact-sheet.jpg")
blender_stage(
"render_animation.py",
[
"--input",
glb,
"--output",
out / "side",
"--preview",
"--angle",
"side",
"--size",
320,
"--frame-count",
frames,
],
"side-render",
)
side_files = sorted((out / "side").glob("*.png"))
side_sheet = Image.new("RGB", (320 * len(side_files), 320), "#182830")
for index, path in enumerate(side_files):
with Image.open(path) as image:
side_sheet.paste(image, (index * 320, 0))
side_sheet.save(out / "side-contact-sheet.jpg")
audit = json.loads((selected / "audit" / "audit.json").read_text())
technical_pass = technical_animation_check(audit, frames)
(selected / "audit" / "audit.json").write_text(json.dumps(audit, indent=2))
return {
"animated_glb": str(glb),
"video": str(video),
"blend": str(selected / "animation.blend"),
"retargeting": str(selected / "retargeting.json"),
"repair_selection": str(out / "repair-selection.json"),
"contact_sheet": str(out / "contact-sheet.jpg"),
"contact_sheets": [str(out / "contact-sheet.jpg"), str(out / "side-contact-sheet.jpg")],
"technical_pass": technical_pass,
"audit": str(selected / "audit" / "audit.json"),
"frames": frames,
"fps": 30,
"collision_summary": audit["summary"],
}
def technical_animation_check(audit, frames):
import numpy as np
tracks = np.array([[row[key] for key in sorted(row)] for row in audit["joints"]])
movement = float(np.linalg.norm(tracks - tracks[:1], axis=2).max())
summary = audit["summary"]
technical_pass = bool(
summary["frames"] == frames
and len(tracks) == frames
and summary["peak_new_pairs"] == 0
and summary["ground_min_z"] >= -1e-5
and summary.get("ground_min_all_vertices_z", summary["ground_min_z"]) >= -1e-5
and np.isfinite(tracks).all()
and movement > 0.01
)
summary["maximum_joint_displacement"] = movement
summary["technical_pass"] = technical_pass
return technical_pass
def repair_improves(baseline, candidate, frames):
"""Choose a repair only when geometry improves without sacrificing sampled motion."""
import numpy as np
def tracks(audit):
names = sorted(audit["joints"][0])
values = np.array([[row[name] for name in names] for row in audit["joints"]])
anchor = names.index("Head") if "Head" in names else 0
return values - values[:, anchor : anchor + 1], float(
np.linalg.norm(values - values[:1], axis=2).max()
)
(before, before_motion), (after, after_motion) = tracks(baseline), tracks(candidate)
compatible = before.shape == after.shape and len(after) == frames
finite = bool(np.isfinite(after).all())
difference = float(np.linalg.norm(after - before, axis=2).max()) if compatible else float("inf")
left, right = baseline["summary"], candidate["summary"]
checks = {
"all_frames_finite": compatible and finite,
"motion_preserved": compatible
and finite
and difference <= 1e-4
and after_motion >= max(0.01, before_motion * 0.95),
"maximum_relative_joint_difference": difference,
"fewer_intersections": right["peak_new_pairs"] < left["peak_new_pairs"],
"no_rest_regression": right.get("rest_intersections", 0) <= left.get("rest_intersections", 0),
"no_deeper_crossings": right["peak_triangle_plane_depth"] <= left["peak_triangle_plane_depth"] + 1e-6,
"no_more_affected_surface": right["peak_affected_surface_fraction"]
<= left["peak_affected_surface_fraction"] + 1e-6,
"no_ground_regression": right["ground_min_all_vertices_z"]
>= min(left["ground_min_all_vertices_z"], -1e-5) - 1e-6,
}
accepted = all(value for key, value in checks.items() if key != "maximum_relative_joint_difference")
return bool(accepted), checks
|