dreevelleandClaude Opus 5
be47c0be20
[tool.comfy] Icon gets the raw GitHub URL for the assets/icon.png added
in the previous commit. It is already live on main and serving 200, so
the registry has something to resolve the moment this lands.
The version bump carries no functional change and exists only to deliver
the icon. icon is node-level metadata that the registry writes as a side
effect of publishing a version -- comfy-cli sends it inside the node
object of POST /publishers/{id}/nodes/{id}/versions -- and an existing
version cannot be re-pushed, so a bump is the only way an icon reaches a
node that has already published.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015p88qHFcfungDkCbG1n7z2
ComfyUI-FastImageSequence
A fast PNG image-sequence saver for ComfyUI.
The built-in Save Image (Advanced) node encodes each frame of a batch one at a time. For long sequences (video / frame dumps) that's slow — almost all the time goes into single-threaded zlib PNG compression, not metadata.
This node encodes the frames of a batch in parallel. PyAV releases the GIL during compression, so encoding scales with your CPU cores. The output bytes are identical to the built-in node — same pixels, same compression, same file size — it's just much faster.
It also embeds the prompt/workflow metadata in only the first frame by default, so the workflow is still recoverable from the sequence without bloating every single frame.
Node
Save Image Sequence (Fast 16-bit) (category: image)
| Input | Default | Notes |
|---|---|---|
images |
— | The image batch to save. |
filename_prefix |
ComfyUI |
Supports the usual tokens (%date:yyyy-MM-dd%, etc.). |
bit_depth |
16-bit |
8-bit or 16-bit PNG. |
metadata (advanced) |
first_frame |
first_frame / all / none. |
threads (advanced) |
0 (auto) |
Encoder threads. 0 = min(8, CPU count). |
Drop it in wherever you'd use Save Image (Advanced). It handles the whole batch itself, including the first-frame metadata, so wire the entire sequence into this one node (don't split it across two save nodes — that would collide on the sequential file numbering).
Performance
Measured on a 16-core CPU, 457 frames at 1920×1088, 16-bit RGB (worst-case noisy content; real frames are faster):
| threads | ms/frame | 457 frames |
|---|---|---|
| 1 (built-in, serial) | 372 | ~170 s |
| 4 | 101 | ~46 s |
| 8 (auto default) | 60 | ~27 s |
| 16 | 43 | ~20 s |
| 24 | 44 | ~20 s (no gain) |
Scaling flattens at your core count — there's no benefit to setting threads
higher than the number of CPU cores. 0 (auto = 8) already captures most of the
win; set it to your core count for the last few seconds.
For reference, metadata injection costs ~0.9 ms/frame (~0.2% of the total), so
the metadata option is about file size / cleanliness, not speed.
Installation
Clone into your ComfyUI custom_nodes directory and restart:
cd ComfyUI/custom_nodes
git clone https://github.com/dreevelle/ComfyUI-FastImageSequence.git
av, numpy and torch ship with ComfyUI, so there are no extra dependencies
to install.
Notes
- Output is byte-identical to Save Image (Advanced) for the same input — this node only changes how fast the frames are written, not the result.
- True 16-bit PNGs (IHDR bit depth 16). Note that Pillow downsamples 16-bit
color PNGs to 8-bit when reading them, so a
PIL.Image.open(...).modecheck will reportRGBeven though the file on disk is genuinely 16-bit. - Self-contained: it copies the small PNG encode/metadata helpers rather than importing from ComfyUI internals, so a core update won't break it.