PIL.Image.fromarray accepts 2-channel (LA mode) arrays as well, not
just 1/3/4-channel. Reword the inline comments and test docstrings to
say 'rejects > 4-channel arrays', which is the actual constraint
driving the cap. Also drop a too-narrow 'mode in (L, RGB, RGBA)'
assertion in test_save_compatible_output_passes_through_pil so a
future 2-channel result would not be flagged as a failure.
Address review feedback: the previous fix allowed ImageBlend to return
tensors with > 4 channels (e.g. blending a 3-channel and a 5-channel
image produced a 5-channel tensor). This shifted the original failure
from blend-time to save/preview-time, because SaveImage and PreviewImage
both call PIL.Image.fromarray, which only supports 1/3/4-channel arrays.
Fix:
- In Blend.execute, the alignment target is now min(max(c1, c2), 4):
any image with more than 4 channels is truncated, any image with
fewer is padded with 1.0s up to the (capped) target. This makes the
RGB/RGBA case work and also makes the >4-channel case work end-to-end
rather than just deferring its failure.
- Update the regression test that previously codified the wrong
5-channel-output behavior to assert the correct 4-channel cap.
- Add test_output_capped_at_four_channels (both inputs > 4 channels).
- Add test_save_compatible_output_passes_through_pil that mirrors
SaveImage's exact PIL.Image.fromarray conversion to catch regressions
in the save/preview path.
- Add a small workflow-validation test (image_blend_workflow_test.py)
that loads tests/inference/graphs/image_blend_channel_mismatch.json
and verifies its node types and wiring, so the demo workflow can't
silently bitrot.
Verified end-to-end against a local ComfyUI server: the workflow runs,
output is RGBA, downstream SaveImage succeeds.
- Add regression tests covering RGB+RGBA, RGBA+RGB, channel gap > 1
(the exact CORE-103 error case), all blend modes with mismatch, and
output value clamping.
- Soften the inline comment to reflect that channel padding is well-
defined for alpha-like extra channels rather than claiming support
for arbitrary channel layouts.
Replace the limited node_helpers.image_alpha_fix call (which only handles
RGB<->RGBA differences by padding by exactly one channel) with the same
generalized channel-padding logic used by the ImageStitch node.
This allows ImageBlend to work with any combination of channel counts
(e.g. 3 vs 4, 3 vs 5, 4 vs 3, etc.) by padding the image with fewer
channels using 1.0s up to the larger channel count. Behavior between
ImageBlend and ImageStitch is now consistent.
Fixes CORE-103.
* feat: add essentials_category to nodes and blueprints for Essentials tab
Add ESSENTIALS_CATEGORY or essentials_category to 12 node classes and all
36 blueprint JSONs. Update SubgraphEntry TypedDict and subgraph_manager to
extract and pass through the field.
Fixes COM-15221
Amp-Thread-ID: https://ampcode.com/threads/T-019c83de-f7ab-7779-a451-0ba5940b56a9
* fix: import NotRequired from typing_extensions for Python 3.10 compat
* refactor: keep only node class ESSENTIALS_CATEGORY, remove blueprint/subgraph changes
Frontend will own blueprint categorization separately.
* fix: remove essentials_category from CreateVideo (not in spec)
---------
Co-authored-by: guill <jacob.e.segal@gmail.com>
Move essentials_category from deprecated/incorrect nodes to their replacements:
- ImageBatch → BatchImagesNode (ImageBatch is deprecated)
- Blur → removed (should use subgraph blueprint)
- GetVideoComponents → Video Slice
Amp-Thread-ID: https://ampcode.com/threads/T-019c8340-4da2-723b-a09f-83895c5bbda5
Add 24 non-cloud essential blueprints from comfyui-wiki/Subgraph-Blueprints.
These cover common workflows: text/image/video generation, editing,
inpainting, outpainting, upscaling, depth maps, pose, captioning, and more.
Cloud-only blueprints (5) are excluded and will be added once
client-side distribution filtering lands.
Amp-Thread-ID: https://ampcode.com/threads/T-019c6f43-6212-7308-bea6-bfc35a486cbf
- Add search_aliases for discoverability: resize, scale, dimensions, etc.
- Add node description for hover tooltip
- Add tooltips to all inputs explaining their behavior
- Reorder options: most common (scale dimensions) first, most technical (scale to multiple) last
Addresses user feedback that 'resize' search returned nothing useful and
options like 'match size' and 'scale to multiple' were not self-explanatory.
- Add search_aliases for discoverability: resize, scale, dimensions, etc.
- Add node description for hover tooltip
- Add tooltips to all inputs explaining their behavior
- Reorder options: most common (scale dimensions) first, most technical (scale to multiple) last
Addresses user feedback that 'resize' search returned nothing useful and
options like 'match size' and 'scale to multiple' were not self-explanatory.
* Support Combo outputs in a more sane way
* Remove test validate_inputs function on test node
* Make curr_prefix be a list of strings instead of string for easier parsing as keys get added to dynamic types
* Start to account for id prefixes from frontend, need to fix bug with nested dynamics
* Ensure inputs/outputs/hidden are lists in schema finalize function, remove no longer needed 'is not None' checks
* Add raw_link and extra_dict to all relevant Inputs
* Make nested DynamicCombos work properly with prefixed keys on latest frontend; breaks old Autogrow, but is pretty much ready for upcoming Autogrow keys
* Replace ... usage with a MISSING sentinel for clarity in nodes_logic.py
* Added CustomCombo node in backend to reflect frontend node
* Prepare Autogrow's expand_schema_for_dynamic to work with upcoming frontend changes
* Prepare for look up table for dynamic input stuff
* More progress towards dynamic input lookup function stuff
* Finished converting _expand_schema_for_dynamic to be done via lookup instead of OOP to guarantee working with process isolation, did refactoring to remove old implementation + cleaning INPUT_TYPES definition including v3 hidden definition
* Change order of functions
* Removed some unneeded functions after dynamic refactor
* Make MatchType's output default displayname "MATCHTYPE"
* Fix DynamicSlot get_all
* Removed redundant code - dynamic stuff no longer happens in OOP way
* Natively support AnyType (*) without __ne__ hacks
* Remove stray code that made it in
* Remove expand_schema_for_dynamic left over on DynamicInput class
* get_dynamic() on DynamicInput/Output was not doing anything anymore, so removed it
* Make validate_inputs validate combo input correctly
* Temporarily comment out conversion to 'new' (9 month old) COMBO format in get_input_info
* Remove refrences to resources feature scrapped from V3
* Expose DynamicCombo in public API
* satisfy ruff after some code got commented out
* Make missing input error prettier for dynamic types
* Created a Switch2 node as a side-by-side test, will likely go with Switch2 as the initial switch node
* Figured out Switch situation
* Pass in v3_data in IsChangedCache.get function's fingerprint_inputs, add a from_v3_data helper method to HiddenHolder
* Switch order of Switch and Soft Switch nodes in file
* Temp test node for MatchType
* Fix missing v3_data for v1 nodes in validation
* For now, remove chacking duplicate id's for dynamic types
* Add Resize Image/Mask node that thanks to MatchType+DynamicCombo is 16-nodes-in-1
* Made DynamicCombo references in DCTestNode use public interface
* Add an AnyTypeTestNode
* Make lazy status for specific inputs on DynamicInputs work by having the values of the dictionary for check_lazy_status be a tuple, where the second element is the key of the input that can be returned
* Comment out test logic nodes
* Make primitive float's step make more sense
* Add (and leave commented out) some potential logic nodes
* Change default crop option to "center" on Resize Image/Mask node
* Changed copy.copy(d) to d.copy()
* Autogrow is available in stable frontend, so exposing it in public API
* Use outputs id as display_name if no display_name present, remove v3 outputs id restriction that made them have to have unique IDs from the inputs
* Enable Custom Combo node as stable frontend now supports it
* Make id properly act like display_name on outputs
* Add Batch Images/Masks/Latents node
* Comment out Batch Images/Masks/Latents node for now, as Autogrow has a bug with MatchType where top connection is disconnected upon refresh
* Removed code for a couple test nodes in nodes_logic.py
* Add Batch Images, Batch Masks, and Batch Latents nodes with Autogrow, deprecate old Batch Images + LatentBatch nodes
