Ethanfel/ComfyUI-SelVA
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

perf: replace MP4 encode/decode with lossless .npy frame transfer

Browse Source 
Saves frames as uint8 .npy instead of H.264 MP4, eliminating the
lossy codec roundtrip. extract_features.py loads .npy directly and
skips decord when given a numpy file. Passes --source_fps for
correct temporal sampling.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Ethanfel
2026-03-28 10:50:35 +01:00
parent c38df8c6fa
commit 707ccb463e
2 changed files with 44 additions and 40 deletions
Download Patch File Download Diff File Expand all files Collapse all files
scripts/extract_features.py
+33 -15
View File
@@ -42,6 +42,7 @@ def main():
parser.add_argument("--output", required=True, help="Output .npz path")
parser.add_argument("--synchformer_ckpt", default=None, help="Path to synchformer checkpoint")
parser.add_argument("--vae_config", default=None, help="Path to VAE config JSON")
parser.add_argument("--source_fps", type=float, default=30.0, help="Original video fps (used when --video is a .npy file)")
parser.add_argument("--clip_fps", type=float, default=4.0)
parser.add_argument("--clip_size", type=int, default=288)
parser.add_argument("--sync_fps", type=float, default=25.0)
@@ -64,7 +65,6 @@ def main():
t0 = _step(1, 6, "importing dependencies")
from data_utils.v2a_utils.feature_utils_288 import FeaturesUtils
import torchvision.transforms as T
from decord import VideoReader, cpu
_done(t0)
# ------------------------------------------------------------------
@@ -78,16 +78,39 @@ def main():
# ------------------------------------------------------------------
t0 = _step(3, 6, "reading and preprocessing video")
vr = VideoReader(args.video, ctx=cpu(0))
fps = vr.get_avg_fps()
total_frames = len(vr)
duration = total_frames / fps
print(f"[extract] fps={fps:.3f} frames={total_frames} duration={duration:.2f}s", flush=True)
if args.video.endswith(".npy"):
all_frames = np.load(args.video) # [T, H, W, C] uint8
fps = args.source_fps
total_frames = all_frames.shape[0]
duration = total_frames / fps
print(f"[extract] fps={fps:.3f} frames={total_frames} duration={duration:.2f}s", flush=True)
clip_indices = [int(i * fps / args.clip_fps) for i in range(int(duration * args.clip_fps))]
clip_indices = [min(i, total_frames - 1) for i in clip_indices]
clip_frames = vr.get_batch(clip_indices).asnumpy()
print(f"[extract] CLIP frames : {len(clip_indices)} @ {args.clip_fps}fps → {args.clip_size}×{args.clip_size}", flush=True)
clip_indices = [int(i * fps / args.clip_fps) for i in range(int(duration * args.clip_fps))]
clip_indices = [min(i, total_frames - 1) for i in clip_indices]
clip_frames = all_frames[clip_indices]
print(f"[extract] CLIP frames : {len(clip_indices)} @ {args.clip_fps}fps → {args.clip_size}×{args.clip_size}", flush=True)
sync_indices = [int(i * fps / args.sync_fps) for i in range(int(duration * args.sync_fps))]
sync_indices = [min(i, total_frames - 1) for i in sync_indices]
sync_frames = all_frames[sync_indices]
print(f"[extract] Sync frames : {len(sync_indices)} @ {args.sync_fps}fps → {args.sync_size}×{args.sync_size}", flush=True)
else:
from decord import VideoReader, cpu
vr = VideoReader(args.video, ctx=cpu(0))
fps = vr.get_avg_fps()
total_frames = len(vr)
duration = total_frames / fps
print(f"[extract] fps={fps:.3f} frames={total_frames} duration={duration:.2f}s", flush=True)
clip_indices = [int(i * fps / args.clip_fps) for i in range(int(duration * args.clip_fps))]
clip_indices = [min(i, total_frames - 1) for i in clip_indices]
clip_frames = vr.get_batch(clip_indices).asnumpy()
print(f"[extract] CLIP frames : {len(clip_indices)} @ {args.clip_fps}fps → {args.clip_size}×{args.clip_size}", flush=True)
sync_indices = [int(i * fps / args.sync_fps) for i in range(int(duration * args.sync_fps))]
sync_indices = [min(i, total_frames - 1) for i in sync_indices]
sync_frames = vr.get_batch(sync_indices).asnumpy()
print(f"[extract] Sync frames : {len(sync_indices)} @ {args.sync_fps}fps → {args.sync_size}×{args.sync_size}", flush=True)
clip_transform = T.Compose([
T.ToPILImage(),
@@ -98,11 +121,6 @@ def main():
])
clip_input = torch.stack([clip_transform(f) for f in clip_frames]).unsqueeze(0).to(device)
sync_indices = [int(i * fps / args.sync_fps) for i in range(int(duration * args.sync_fps))]
sync_indices = [min(i, total_frames - 1) for i in sync_indices]
sync_frames = vr.get_batch(sync_indices).asnumpy()
print(f"[extract] Sync frames : {len(sync_indices)} @ {args.sync_fps}fps → {args.sync_size}×{args.sync_size}", flush=True)
sync_transform = T.Compose([
T.ToPILImage(),
T.Resize(args.sync_size),