new_share_long_live_100 / scripts /prepare_spatialvid_csv.py
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#!/usr/bin/env python3
"""Build a LiveWorld four-field CSV from SpatialVID_preped.
SpatialVID / LongLive i2v assets:
- sampled_clippath.csv -> prompt + clipPath
- <video_root>/<clipPath> -> first-frame image
- clip_annotation/<stem>/longlive/scene_projection_input.mp4 (81 frames)
- clip_annotation/<stem>/longlive/fg_projection_input.mp4 (81 frames)
LiveWorld ``condition_source=mp4`` with ``num_frames=81`` indexes projection
videos at global indices ``1..81`` (first_frame is separate at index 0).
So an 81-frame LongLive control must be padded to 82 frames:
lw_proj = [pad_frame] + longlive_proj[0..80]
then LiveWorld targets ``1..81`` consume the original 81 LongLive frames.
Pad policy:
- bg: first frame of the source clip (same as input_image)
- fg: black frame (FG at t=0 lives in the RGB image)
Writes per stem under ``--output-root/<stem>/``:
first_frame.png, bg_projection.mp4, fg_projection.mp4
and a CSV (paths relative to the CSV file location):
name,input_image,text,bg_projection,fg_projection
"""
from __future__ import annotations
import argparse
import csv
import sys
from pathlib import Path
from typing import Optional, Tuple
import cv2
import numpy as np
from tqdm import tqdm
def parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser(description=__doc__)
p.add_argument(
"--csv",
type=Path,
default=Path(
"/home/zhangzhiyuan/VAM_projs/realbench_comp/"
"SpatialVID_preped/sampled_clippath.csv"
),
)
p.add_argument(
"--video-root",
type=Path,
default=Path(
"/home/zhangzhiyuan/VAM_projs/realbench_comp/SpatialVID_preped"
),
help="Directory containing <clipPath> mp4s",
)
p.add_argument(
"--annotation-root",
type=Path,
default=Path(
"/home/zhangzhiyuan/VAM_projs/realbench_comp/"
"SpatialVID_preped/clip_annotation"
),
)
p.add_argument(
"--output-root",
type=Path,
default=Path(__file__).resolve().parents[1] / "liveworld_i2v_inputs",
help="Per-case first_frame + padded 82-frame projections "
"(default: LiveWorld_comp/liveworld_i2v_inputs)",
)
p.add_argument(
"--out-csv",
type=Path,
default=Path(__file__).resolve().parents[1] / "liveworld_i2v_cases.csv",
help="Output CSV path (default: LiveWorld_comp/liveworld_i2v_cases.csv)",
)
p.add_argument("--fps", type=float, default=16.0,
help="FPS for written projection mp4s (LiveWorld default 16)")
p.add_argument("--target-hw", type=int, nargs=2, default=[480, 832],
metavar=("H", "W"),
help="Resize first_frame / projections to this HxW")
p.add_argument("--overwrite", action="store_true")
p.add_argument("--limit", type=int, default=None)
p.add_argument("--stems", nargs="*", default=None,
help="Only process these stems (default: all csv rows)")
return p.parse_args()
def read_video_bgr(path: Path) -> list:
cap = cv2.VideoCapture(str(path))
if not cap.isOpened():
raise FileNotFoundError(f"cannot open video: {path}")
frames = []
while True:
ok, frame = cap.read()
if not ok:
break
frames.append(frame)
cap.release()
if not frames:
raise RuntimeError(f"empty video: {path}")
return frames
def write_video_bgr(path: Path, frames: list, fps: float) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
h, w = frames[0].shape[:2]
writer = cv2.VideoWriter(
str(path),
cv2.VideoWriter_fourcc(*"mp4v"),
float(fps),
(w, h),
)
if not writer.isOpened():
raise RuntimeError(f"failed to open VideoWriter: {path}")
for f in frames:
writer.write(f)
writer.release()
def resize_bgr(frame: np.ndarray, target_hw: Tuple[int, int]) -> np.ndarray:
H, W = target_hw
if frame.shape[0] == H and frame.shape[1] == W:
return frame
return cv2.resize(frame, (W, H), interpolation=cv2.INTER_LINEAR)
def pad_projection_to_82(
frames_81: list,
pad_frame: np.ndarray,
target_hw: Tuple[int, int],
) -> list:
"""Prepend pad_frame so LiveWorld indices 1..81 map to original 0..80."""
if len(frames_81) != 81:
raise ValueError(f"expected 81 frames, got {len(frames_81)}")
pad = resize_bgr(pad_frame, target_hw)
body = [resize_bgr(f, target_hw) for f in frames_81]
return [pad] + body
def process_one(
stem: str,
prompt: str,
video_path: Path,
annotation_root: Path,
output_root: Path,
fps: float,
target_hw: Tuple[int, int],
overwrite: bool,
) -> Optional[dict]:
ll_dir = annotation_root / stem / "longlive"
bg_src = ll_dir / "scene_projection_input.mp4"
fg_src = ll_dir / "fg_projection_input.mp4"
if not bg_src.exists() or not fg_src.exists():
print(f"[skip] missing projections: {stem}", file=sys.stderr)
return None
if not video_path.exists():
print(f"[skip] missing video: {video_path}", file=sys.stderr)
return None
out_dir = output_root / stem
first_path = out_dir / "first_frame.png"
bg_out = out_dir / "bg_projection.mp4"
fg_out = out_dir / "fg_projection.mp4"
if (
not overwrite
and first_path.exists()
and bg_out.exists()
and fg_out.exists()
):
return {
"name": stem,
"input_image": first_path,
"text": prompt,
"bg_projection": bg_out,
"fg_projection": fg_out,
}
src_frames = read_video_bgr(video_path)
first_bgr = resize_bgr(src_frames[0], target_hw)
out_dir.mkdir(parents=True, exist_ok=True)
cv2.imwrite(str(first_path), first_bgr)
bg_81 = read_video_bgr(bg_src)
fg_81 = read_video_bgr(fg_src)
if len(bg_81) != 81 or len(fg_81) != 81:
print(
f"[skip] {stem}: expected 81-frame projections, "
f"got bg={len(bg_81)} fg={len(fg_81)}",
file=sys.stderr,
)
return None
H, W = target_hw
black = np.zeros((H, W, 3), dtype=np.uint8)
bg_82 = pad_projection_to_82(bg_81, first_bgr, target_hw)
fg_82 = pad_projection_to_82(fg_81, black, target_hw)
write_video_bgr(bg_out, bg_82, fps)
write_video_bgr(fg_out, fg_82, fps)
return {
"name": stem,
"input_image": first_path,
"text": prompt,
"bg_projection": bg_out,
"fg_projection": fg_out,
}
def main() -> None:
args = parse_args()
target_hw = (int(args.target_hw[0]), int(args.target_hw[1]))
wanted = set(args.stems) if args.stems else None
with args.csv.open("r", encoding="utf-8-sig", newline="") as f:
rows = list(csv.DictReader(f))
if not rows:
raise SystemExit(f"empty csv: {args.csv}")
selected = []
for r in rows:
clip = (r.get("clipPath") or "").strip()
if not clip:
continue
stem = Path(clip).stem
if wanted is not None and stem not in wanted:
continue
selected.append((stem, (r.get("prompt") or "").strip(), clip))
if args.limit is not None:
selected = selected[: args.limit]
args.output_root.mkdir(parents=True, exist_ok=True)
out_rows = []
n_fail = 0
for stem, prompt, clip in tqdm(selected, desc="prepare liveworld i2v"):
if not prompt:
print(f"[skip] empty prompt: {stem}", file=sys.stderr)
n_fail += 1
continue
video_path = args.video_root / clip
try:
row = process_one(
stem=stem,
prompt=prompt,
video_path=video_path,
annotation_root=args.annotation_root,
output_root=args.output_root,
fps=args.fps,
target_hw=target_hw,
overwrite=args.overwrite,
)
except Exception as e: # noqa: BLE001
n_fail += 1
print(f"[FAIL] {stem}: {e}", file=sys.stderr)
continue
if row is None:
n_fail += 1
continue
out_rows.append(row)
args.out_csv.parent.mkdir(parents=True, exist_ok=True)
csv_base = args.out_csv.resolve().parent
def _rel(p: Path) -> str:
try:
return str(p.resolve().relative_to(csv_base))
except ValueError:
return str(p.resolve())
csv_rows = [
{
"name": r["name"],
"input_image": _rel(Path(r["input_image"])),
"text": r["text"],
"bg_projection": _rel(Path(r["bg_projection"])),
"fg_projection": _rel(Path(r["fg_projection"])),
}
for r in out_rows
]
with args.out_csv.open("w", encoding="utf-8", newline="") as f:
writer = csv.DictWriter(
f,
fieldnames=[
"name", "input_image", "text", "bg_projection", "fg_projection",
],
quoting=csv.QUOTE_MINIMAL,
)
writer.writeheader()
writer.writerows(csv_rows)
print(
f"[done] wrote {len(csv_rows)} rows -> {args.out_csv} "
f"(fail/skip={n_fail}, inputs={args.output_root})"
)
if __name__ == "__main__":
main()