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perf: reuse guide images and drag selections

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This commit is contained in:
OpenClaw Agent
2026-07-09 20:44:38 +00:00
parent 50664026a1
commit e87b5d8d8f
2 changed files with 54 additions and 35 deletions
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6
js/ltx_director.js
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@@ -8189,13 +8189,13 @@ class TimelineEditor {
return s; return s;
}), }),
motion: this._multiDragInitialSegments.motion.map(s => { motion: this._multiDragInitialSegments.motion.map(s => {
if (selectedIds.includes(s.id)) { if (selectedIdSet.has(s.id)) {
return { ...s, start: s.start + clampedDragDelta }; return { ...s, start: s.start + clampedDragDelta };
} }
return s; return s;
}), }),
audio: this._multiDragInitialSegments.audio.map(s => { audio: this._multiDragInitialSegments.audio.map(s => {
if (selectedIds.includes(s.id)) { if (selectedIdSet.has(s.id)) {
return { ...s, start: s.start + clampedDragDelta }; return { ...s, start: s.start + clampedDragDelta };
} }
return s; return s;
@@ -8206,7 +8206,7 @@ class TimelineEditor {
for (const track of ["image", "motion"]) { for (const track of ["image", "motion"]) {
const prevSegs = this._multiDragPreviewTimelines[track]; const prevSegs = this._multiDragPreviewTimelines[track];
for (const s of prevSegs) { for (const s of prevSegs) {
if (selectedIds.includes(s.id) && (s.type === "video" || s.type === "motion_video")) { if (selectedIdSet.has(s.id) && (s.type === "video" || s.type === "motion_video")) {
this._liveScrubVideo(s, "start"); this._liveScrubVideo(s, "start");
} }
} }

47
ltx_director.py
View File

@@ -1207,6 +1207,7 @@ def _build_guide_data_from_timeline(
): ):
guide_data = {"images": [], "insert_frames": [], "strengths": [], "frame_rate": frame_rate_f} guide_data = {"images": [], "insert_frames": [], "strengths": [], "frame_rate": frame_rate_f}
derived_w, derived_h = custom_width, custom_height derived_w, derived_h = custom_width, custom_height
processed_still_cache = {}
try: try:
img_segs = [ img_segs = [
@@ -1234,23 +1235,41 @@ def _build_guide_data_from_timeline(
seg_for_load["trimStart"] = float(seg.get("trimStart", 0)) + offset seg_for_load["trimStart"] = float(seg.get("trimStart", 0)) + offset
seg_for_load["length"] = max(1, seg_length - offset) seg_for_load["length"] = max(1, seg_length - offset)
tensor = _load_video_tensor(seg_for_load, frame_rate_f, input_dir=input_dir) tensor = _load_video_tensor(seg_for_load, frame_rate_f, input_dir=input_dir)
cache_key = None
else: else:
tensor = _load_image_tensor(seg, cache=image_cache, input_dir=input_dir) cache_key = (
seg.get("imageFile") or "",
seg.get("imageB64") or "",
custom_width,
custom_height,
resize_method,
divisible_by,
img_compression,
)
cached_tensor = processed_still_cache.get(cache_key)
if cached_tensor is not None:
tensor = cached_tensor
else:
tensor = _load_image_tensor(seg, cache=image_cache, input_dir=input_dir)
src_h, src_w = tensor.shape[1], tensor.shape[2] if cache_key is None or cached_tensor is None:
tgt_w, tgt_h, resize_override = _target_resize_dims( src_h, src_w = tensor.shape[1], tensor.shape[2]
src_w, src_h, custom_width, custom_height, divisible_by tgt_w, tgt_h, resize_override = _target_resize_dims(
) src_w, src_h, custom_width, custom_height, divisible_by
tensor = _resize_image( )
tensor, tensor = _resize_image(
tgt_w, tensor,
tgt_h, tgt_w,
resize_override or resize_method, tgt_h,
divisible_by, resize_override or resize_method,
) divisible_by,
)
if img_compression > 0: if img_compression > 0:
tensor = _compress_image(tensor, img_compression) tensor = _compress_image(tensor, img_compression)
if cache_key is not None:
processed_still_cache[cache_key] = tensor
if idx == 0: if idx == 0:
derived_h = tensor.shape[1] derived_h = tensor.shape[1]