index_timestep_zero can be selected in the
FluxKontextMultiReferenceLatentMethod now with the display name set to the
more generic "Edit Model Reference Method" node.
The inpaint part is currently missing and will be implemented later.
I think they messed up this model pretty bad. They added some
control_noise_refiner blocks but don't actually use them. There is a typo
in their code so instead of doing control_noise_refiner -> control_layers
it runs the whole control_layers twice.
Unfortunately they trained with this typo so the model works but is kind
of slow and would probably perform a lot better if they corrected their
code and trained it again.
* Add Kandinsky5 model support
lite and pro T2V tested to work
* Update kandinsky5.py
* Fix fp8
* Fix fp8_scaled text encoder
* Add transformer_options for attention
* Code cleanup, optimizations, use fp32 for all layers originally at fp32
* ImageToVideo -node
* Fix I2V, add necessary latent post process nodes
* Support text to image model
* Support block replace patches (SLG mostly)
* Support official LoRAs
* Don't scale RoPE for lite model as that just doesn't work...
* Update supported_models.py
* Rever RoPE scaling to simpler one
* Fix typo
* Handle latent dim difference for image model in the VAE instead
* Add node to use different prompts for clip_l and qwen25_7b
* Reduce peak VRAM usage a bit
* Further reduce peak VRAM consumption by chunking ffn
* Update chunking
* Update memory_usage_factor
* Code cleanup, don't force the fp32 layers as it has minimal effect
* Allow for stronger changes with first frames normalization
Default values are too weak for any meaningful changes, these should probably be exposed as advanced node options when that's available.
* Add image model's own chat template, remove unused image2video template
* Remove hard error in ReplaceVideoLatentFrames -node
* Update kandinsky5.py
* Update supported_models.py
* Fix typos in prompt template
They were now fixed in the original repository as well
* Update ReplaceVideoLatentFrames
Add tooltips
Make source optional
Better handle negative index
* Rename NormalizeVideoLatentFrames -node
For bit better clarity what it does
* Fix NormalizeVideoLatentStart node out on non-op
* Apply cond slice fix
* Add FreeNoise
* Update context_windows.py
* Add option to retain condition by indexes for each window
This allows for example Wan/HunyuanVideo image to video to "work" by using the initial start frame for each window, otherwise windows beyond first will be pure T2V generations.
* Update context_windows.py
* Allow splitting multiple conds into different windows
* Add handling for audio_embed
* whitespace
* Allow freenoise to work on other dims, handle 4D batch timestep
Refactor Freenoise function. And fix batch handling as timesteps seem to be expanded to batch size now.
* Disable experimental options for now
So that the Freenoise and bugfixes can be merged first
---------
Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
Co-authored-by: ozbayb <17261091+ozbayb@users.noreply.github.com>
* Added output_matchtypes to generated json for v3, initial backend support for MatchType, created nodes_logic.py and added SwitchNode
* Fixed providing list of allowed_types
* Add workaround in validation.py for V3 Combo outputs not working as Combo inputs
* Make match type receive_type pass validation
* Also add MatchType check to input_type in validation - will likely trigger when connecting to non-lazy stuff
* Make sure this PR only has MatchType stuff
* Initial work on DynamicCombo
* Add get_dynamic function, not yet filled out correctly
* Mark Switch node as Beta
* Make sure other unfinished dynamic types are not accidentally used
* Send DynamicCombo.Option inputs in the same format as normal v1 inputs
* add dynamic combo test node
* Support validation of inputs and outputs
* Add missing input params to DynamicCombo.Input
* Add get_all function to inputs for id validation purposes
* Fix imports for v3 returning everything when doing io/ui/IO/UI instead of what is in __all__ of _io.py and _ui.py
* Modifying behavior of get_dynamic in V3 + serialization so can be used in execution code
* Fix v3 schema validation code after changes
* Refactor hidden_values for v3 in execution.py to be more general v3_data, add helper functions for dynamic behavior, preparing for restructuring dynamic type into object (not finished yet)
* Add nesting of inputs on DynamicCombo during execution
* Work with latest frontend commits
* Fix cringe arrows
* frontend will no longer namespace dynamic inputs widgets so reflect that in code, refactor build_nested_inputs
* Prepare Autogrow support for the love of the game
* satisfy ruff
* Create test nodes for Autogrow to collab with frontend development
* Add nested combo to DCTestNode
* Remove array support from build_nested_inputs, properly handle missing expected values
* Make execution.validate_inputs properly validate required dynamic inputs, renamed dynamic_data to dynamic_paths for clarity
* MatchType does not need any DynamicInput/Output features on backend; will increase compatibility with dynamic types
* Probably need this for ruff check
* Change MatchType to have template be the first and only required param; output id's do nothing right now, so no need
* Fix merge regression with LatentUpscaleModel type not being put in __all__ for _io.py, fix invalid type hint for validate_inputs
* Make Switch node inputs optional, disallow both inputs from being missing, and still work properly with lazy; when one input is missing, use the other no matter what the switch is set to
* Satisfy ruff
* Move MatchType code above the types that inherit from DynamicInput
* Add DynamicSlot type, awaiting frontend support
* Make curr_prefix creation happen in Autogrow, move curr_prefix in DynamicCombo to only be created if input exists in live_inputs
* I was confused, fixing accidentally redundant curr_prefix addition in Autogrow
* Make sure Autogrow inputs are force_input = True when WidgetInput, fix runtime validation by removing original input from expected inputs, fix min/max bounds, change test nodes slightly
* Remove unnecessary id usage in Autogrow test node outputs
* Commented out Switch node + test nodes
* Remove commented out code from Autogrow
* Make TemplatePrefix max more clear, allow max == 1
* Replace all dict[str] with dict[str, Any]
* Renamed add_to_dict_live_inputs to expand_schema_for_dynamic
* Fixed typo in DynamicSlot input code
* note about live_inputs not being present soon in get_v1_info (internal function anyway)
* For now, hide DynamicCombo and Autogrow from public interface
* Removed comment
These are not actual controlnets so put it in the models/model_patches
folder and use the ModelPatchLoader + QwenImageDiffsynthControlnet node to
use it.
* Create nodes_dataset.py
* Add encoded dataset caching mechanism
* make training node to work with our dataset system
* allow trainer node to get different resolution dataset
* move all dataset related implementation to nodes_dataset
* Rewrite dataset system with new io schema
* Rewrite training system with new io schema
* add ui pbar
* Add outputs' id/name
* Fix bad id/naming
* use single process instead of input list when no need
* fix wrong output_list flag
* use torch.load/save and fix bad behaviors
* init
* update
* Update model.py
* Update model.py
* remove print
* Fix text encoding
* Prevent empty negative prompt
Really doesn't work otherwise
* fp16 works
* I2V
* Update model_base.py
* Update nodes_hunyuan.py
* Better latent rgb factors
* Use the correct sigclip output...
* Support HunyuanVideo1.5 SR model
* whitespaces...
* Proper latent channel count
* SR model fixes
This also still needs timesteps scheduling based on the noise scale, can be used with two samplers too already
* vae_refiner: roll the convolution through temporal
Work in progress.
Roll the convolution through time using 2-latent-frame chunks and a
FIFO queue for the convolution seams.
* Support HunyuanVideo15 latent resampler
* fix
* Some cleanup
Co-Authored-By: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
* Proper hyvid15 I2V channels
Co-Authored-By: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
* Fix TokenRefiner for fp16
Otherwise x.sum has infs, just in case only casting if input is fp16, I don't know if necessary.
* Bugfix for the HunyuanVideo15 SR model
* vae_refiner: roll the convolution through temporal II
Roll the convolution through time using 2-latent-frame chunks and a
FIFO queue for the convolution seams.
Added support for encoder, lowered to 1 latent frame to save more
VRAM, made work for Hunyuan Image 3.0 (as code shared).
Fixed names, cleaned up code.
* Allow any number of input frames in VAE.
* Better VAE encode mem estimation.
* Lowvram fix.
* Fix hunyuan image 2.1 refiner.
* Fix mistake.
* Name changes.
* Rename.
* Whitespace.
* Fix.
* Fix.
---------
Co-authored-by: kijai <40791699+kijai@users.noreply.github.com>
Co-authored-by: Rattus <rattus128@gmail.com>
Slices model input with output channels so the caching tracks only the noise channels, resolves channel mismatch with models like WanVideo I2V
Also fix for slicing deprecation in pytorch 2.9
* Initial Chroma Radiance support
* Minor Chroma Radiance cleanups
* Update Radiance nodes to ensure latents/images are on the intermediate device
* Fix Chroma Radiance memory estimation.
* Increase Chroma Radiance memory usage factor
* Increase Chroma Radiance memory usage factor once again
* Ensure images are multiples of 16 for Chroma Radiance
Add batch dimension and fix channels when necessary in ChromaRadianceImageToLatent node
* Tile Chroma Radiance NeRF to reduce memory consumption, update memory usage factor
* Update Radiance to support conv nerf final head type.
* Allow setting NeRF embedder dtype for Radiance
Bump Radiance nerf tile size to 32
Support EasyCache/LazyCache on Radiance (maybe)
* Add ChromaRadianceStubVAE node
* Crop Radiance image inputs to multiples of 16 instead of erroring to be in line with existing VAE behavior
* Convert Chroma Radiance nodes to V3 schema.
* Add ChromaRadianceOptions node and backend support.
Cleanups/refactoring to reduce code duplication with Chroma.
* Fix overriding the NeRF embedder dtype for Chroma Radiance
* Minor Chroma Radiance cleanups
* Move Chroma Radiance to its own directory in ldm
Minor code cleanups and tooltip improvements
* Fix Chroma Radiance embedder dtype overriding
* Remove Radiance dynamic nerf_embedder dtype override feature
* Unbork Radiance NeRF embedder init
* Remove Chroma Radiance image conversion and stub VAE nodes
Add a chroma_radiance option to the VAELoader builtin node which uses comfy.sd.PixelspaceConversionVAE
Add a PixelspaceConversionVAE to comfy.sd for converting BHWC 0..1 <-> BCHW -1..1
Load the projector.safetensors file with the ModelPatchLoader node and use
the siglip_vision_patch14_384.safetensors "clip vision" model and the
USOStyleReferenceNode.
* Attempting a universal implementation of EasyCache, starting with flux as test; I screwed up the math a bit, but when I set it just right it works.
* Fixed math to make threshold work as expected, refactored code to use EasyCacheHolder instead of a dict wrapped by object
* Use sigmas from transformer_options instead of timesteps to be compatible with a greater amount of models, make end_percent work
* Make log statement when not skipping useful, preparing for per-cond caching
* Added DIFFUSION_MODEL wrapper around forward function for wan model
* Add subsampling for heuristic inputs
* Add subsampling to output_prev (output_prev_subsampled now)
* Properly consider conds in EasyCache logic
* Created SuperEasyCache to test what happens if caching and reuse is moved outside the scope of conds, added PREDICT_NOISE wrapper to facilitate this test
* Change max reuse_threshold to 3.0
* Mark EasyCache/SuperEasyCache as experimental (beta)
* Make Lumina2 compatible with EasyCache
* Add EasyCache support for Qwen Image
* Fix missing comma, curse you Cursor
* Add EasyCache support to AceStep
* Add EasyCache support to Chroma
* Added EasyCache support to Cosmos Predict t2i
* Make EasyCache not crash with Cosmos Predict ImagToVideo latents, but does not work well at all
* Add EasyCache support to hidream
* Added EasyCache support to hunyuan video
* Added EasyCache support to hunyuan3d
* Added EasyCache support to LTXV (not very good, but does not crash)
* Implemented EasyCache for aura_flow
* Renamed SuperEasyCache to LazyCache, hardcoded subsample_factor to 8 on nodes
* Eatra logging when verbose is true for EasyCache
These are not real controlnets but actually a patch on the model so they
will be treated as such.
Put them in the models/model_patches/ folder.
Use the new ModelPatchLoader and QwenImageDiffsynthControlnet nodes.
* P2 of qwen edit model.
* Typo.
* Fix normal qwen.
* Fix.
* Make the TextEncodeQwenImageEdit also set the ref latent.
If you don't want it to set the ref latent and want to use the
ReferenceLatent node with your custom latent instead just disconnect the
VAE.
This node is only useful if someone trains the kontext model to properly
use multiple reference images via the index method.
The default is the offset method which feeds the multiple images like if
they were stitched together as one. This method works with the current
flux kontext model.
* Added initial support for basic context windows - in progress
* Add prepare_sampling wrapper for context window to more accurately estimate latent memory requirements, fixed merging wrappers/callbacks dicts in prepare_model_patcher
* Made context windows compatible with different dimensions; works for WAN, but results are bad
* Fix comfy.patcher_extension.merge_nested_dicts calls in prepare_model_patcher in sampler_helpers.py
* Considering adding some callbacks to context window code to allow extensions of behavior without the need to rewrite code
* Made dim slicing cleaner
* Add Wan Context WIndows node for testing
* Made context schedule and fuse method functions be stored on the handler instead of needing to be registered in core code to be found
* Moved some code around between node_context_windows.py and context_windows.py
* Change manual context window nodes names/ids
* Added callbacks to IndexListContexHandler
* Adjusted default values for context_length and context_overlap, made schema.inputs definition for WAN Context Windows less annoying
* Make get_resized_cond more robust for various dim sizes
* Fix typo
* Another small fix
* ComfyAPI Core v0.0.2
* Respond to PR feedback
* Fix Python 3.9 errors
* Fix missing backward compatibility proxy
* Reorganize types a bit
The input types, input impls, and utility types are now all available in
the versioned API. See the change in `comfy_extras/nodes_video.py` for
an example of their usage.
* Remove the need for `--generate-api-stubs`
* Fix generated stubs differing by Python version
* Fix ruff formatting issues
* Add factorization utils for lokr
* Add lokr train impl
* Add loha train impl
* Add adapter map for algo selection
* Add optional grad ckpt and algo selection
* Update __init__.py
* correct key name for loha
* Use custom fwd/bwd func and better init for loha
* Support gradient accumulation
* Fix bugs of loha
* use more stable init
* Add OFT training
* linting
* [feat] Add GetImageSize node to return image dimensions
Added a simple GetImageSize node in comfy_extras/nodes_images.py that returns width and height of input images. The node displays dimensions on the UI via PromptServer and provides width/height as outputs for further processing.
* add display name mapping
* [fix] Add server module mock to unit tests for PromptServer import
Updated test to mock server module preventing import errors from the new PromptServer usage in GetImageSize node. Uses direct import pattern consistent with rest of codebase.
* [feat] Add ImageStitch node for concatenating images with borders
Add ImageStitch node that concatenates images in four directions with optional borders and intelligent size handling. Features include optional second image input, configurable borders with color selection, automatic batch size matching, and dimension alignment via padding or resizing.
Upstreamed from https://github.com/kijai/ComfyUI-KJNodes with enhancements for better error handling and comprehensive test coverage.
* [fix] Fix CI issues with CUDA dependencies and linting
- Mock CUDA-dependent modules in tests to avoid CI failures on CPU-only runners
- Fix ruff linting issues for code style compliance
* [fix] Improve CI compatibility by mocking nodes module import
Prevent CUDA initialization chain by mocking the nodes module at import time,
which is cleaner than deep mocking of CUDA-specific functions.
* [refactor] Clean up ImageStitch tests
- Remove unnecessary sys.path manipulation (pythonpath set in pytest.ini)
- Remove metadata tests that test framework internals rather than functionality
- Rename complex scenario test to be more descriptive of what it tests
* [refactor] Rename 'border' to 'spacing' for semantic accuracy
- Change border_width/border_color to spacing_width/spacing_color in API
- Update all tests to use spacing terminology
- Update comments and variable names throughout
- More accurately describes the gap/separator between images
* Make torch compile node use wrapper instead of object_patch for the entire diffusion_models object, allowing key assotiations on diffusion_models to not break (loras, getting attributes, etc.)
* Moved torch compile code into comfy_api so it can be used by custom nodes with a degree of confidence
* Refactor set_torch_compile_wrapper to support a list of keys instead of just diffusion_model, as well as additional torch.compile args
* remove unused import
* Moved torch compile kwargs to be stored in model_options instead of attachments; attachments are more intended for things to be 'persisted', AKA not deepcopied
* Add some comments
* Remove random line of code, not sure how it got there
* support wan camera models
* fix by ruff check
* change camera_condition type; make camera_condition optional
* support camera trajectory nodes
* fix camera direction
---------
Co-authored-by: Qirui Sun <sunqr0667@126.com>
* first pass at opus and mp3 as well as migrating flac to pyav
* minor mp3 encoding fix
* fix ruff
* delete dead code
* split out save audio to separate nodes per filetype
* fix ruff
* Add Ideogram generate node.
* Add staging api.
* Add API_NODE and common error for missing auth token (#5)
* Add Minimax Video Generation + Async Task queue polling example (#6)
* [Minimax] Show video preview and embed workflow in ouput (#7)
* Remove uv.lock
* Remove polling operations.
* Revert "Remove polling operations."
* Update stubs.
* Added Ideogram and Minimax back in.
* Added initial BFL Flux 1.1 [pro] Ultra node (#11)
* Add --comfy-api-base launch arg (#13)
* Add instructions for staging development. (#14)
* remove validation to make it easier to run against LAN copies of the API
* Manually add BFL polling status response schema (#15)
* Add function for uploading files. (#18)
* Add Luma nodes (#16)
* Refactor util functions (#20)
* Add VIDEO type (#21)
* Add rest of Luma node functionality (#19)
* Fix image_luma_ref not working (#28)
* [Bug] Remove duplicated option T2V-01 in MinimaxTextToVideoNode (#31)
* Add utils to map from pydantic model fields to comfy node inputs (#30)
* add veo2, bump av req (#32)
* Add Recraft nodes (#29)
* Add Kling Nodes (#12)
* Add Camera Concepts (luma_concepts) to Luma Video nodes (#33)
* Add Runway nodes (#17)
* Convert Minimax node to use VIDEO output type (#34)
* Standard `CATEGORY` system for api nodes (#35)
* Set `Content-Type` header when uploading files (#36)
* add better error propagation to veo2 (#37)
* Add Realistic Image and Logo Raster styles for Recraft v3 (#38)
* Fix runway image upload and progress polling (#39)
* Fix image upload for Luma: only include `Content-Type` header field if it's set explicitly (#40)
* Moved Luma nodes to nodes_luma.py (#47)
* Moved Recraft nodes to nodes_recraft.py (#48)
* Add Pixverse nodes (#46)
* Move and fix BFL nodes to node_bfl.py (#49)
* Move and edit Minimax node to nodes_minimax.py (#50)
* Add Minimax Image to Video node + Cleanup (#51)
* Add Recraft Text to Vector node, add Save SVG node to handle its output (#53)
* Added pixverse_template support to Pixverse Text to Video node (#54)
* Added Recraft Controls + Recraft Color RGB nodes (#57)
* split remaining nodes out of nodes_api, make utility lib, refactor ideogram (#61)
* Add types and doctstrings to utils file (#64)
* Fix: `PollingOperation` progress bar update progress by absolute value (#65)
* Use common download function in kling nodes module (#67)
* Fix: Luma video nodes in `api nodes/image` category (#68)
* Set request type explicitly (#66)
* Add `control_after_generate` to all seed inputs (#69)
* Fix bug: deleting `Content-Type` when property does not exist (#73)
* Add preview to Save SVG node (#74)
* change default poll interval (#76), rework veo2
* Add Pixverse and updated Kling types (#75)
* Added Pixverse Image to VIdeo node (#77)
* Add Pixverse Transition Video node (#79)
* Proper ray-1-6 support as fix has been applied in backend (#80)
* Added Recraft Style - Infinite Style Library node (#82)
* add ideogram v3 (#83)
* [Kling] Split Camera Control config to its own node (#81)
* Add Pika i2v and t2v nodes (#52)
* Temporary Fix for Runway (#87)
* Added Stability Stable Image Ultra node (#86)
* Remove Runway nodes (#88)
* Fix: Prompt text can't be validated in Kling nodes when using primitive nodes (#90)
* Fix: typo in node name "Stabiliy" => "Stability" (#91)
* Add String (Multiline) node (#93)
* Update Pika Duration and Resolution options (#94)
* Change base branch to master. Not main. (#95)
* Fix UploadRequest file_name param (#98)
* Removed Infinite Style Library until later (#99)
* fix ideogram style types (#100)
* fix multi image return (#101)
* add metadata saving to SVG (#102)
* Bump templates version to include API node template workflows (#104)
* Fix: `download_url_to_video_output` return type (#103)
* fix 4o generation bug (#106)
* Serve SVG files directly (#107)
* Add a bunch of nodes, 3 ready to use, the rest waiting for endpoint support (#108)
* Revert "Serve SVG files directly" (#111)
* Expose 4 remaining Recraft nodes (#112)
* [Kling] Add `Duration` and `Video ID` outputs (#105)
* Fix: datamodel-codegen sets string#binary type to non-existent `bytes_aliased` variable (#114)
* Fix: Dall-e 2 not setting request content-type dynamically (#113)
* Default request timeout: one hour. (#116)
* Add Kling nodes: camera control, start-end frame, lip-sync, video extend (#115)
* Add 8 nodes - 4 BFL, 4 Stability (#117)
* Fix error for Recraft ImageToImage error for nonexistent random_seed param (#118)
* Add remaining Pika nodes (#119)
* Make controls input work for Recraft Image to Image node (#120)
* Use upstream PR: Support saving Comfy VIDEO type to buffer (#123)
* Use Upstream PR: "Fix: Error creating video when sliced audio tensor chunks are non-c-contiguous" (#127)
* Improve audio upload utils (#128)
* Fix: Nested `AnyUrl` in request model cannot be serialized (Kling, Runway) (#129)
* Show errors and API output URLs to the user (change log levels) (#131)
* Fix: Luma I2I fails when weight is <=0.01 (#132)
* Change category of `LumaConcepts` node from image to video (#133)
* Fix: `image.shape` accessed before `image` is null-checked (#134)
* Apply small fixes and most prompt validation (if needed to avoid API error) (#135)
* Node name/category modifications (#140)
* Add back Recraft Style - Infinite Style Library node (#141)
* Fixed Kling: Check attributes of pydantic types. (#144)
* Bump `comfyui-workflow-templates` version (#142)
* [Kling] Print response data when error validating response (#146)
* Fix: error validating Kling image response, trying to use `"key" in` on Pydantic class instance (#147)
* [Kling] Fix: Correct/verify supported subset of input combos in Kling nodes (#149)
* [Kling] Fix typo in node description (#150)
* [Kling] Fix: CFG min/max not being enforced (#151)
* Rebase launch-rebase (private) on prep-branch (public copy of master) (#153)
* Bump templates version (#154)
* Fix: Kling image gen nodes don't return entire batch when `n` > 1 (#152)
* Remove pixverse_template from PixVerse Transition Video node (#155)
* Invert image_weight value on Luma Image to Image node (#156)
* Invert and resize mask for Ideogram V3 node to match masking conventions (#158)
* [Kling] Fix: image generation nodes not returning Tuple (#159)
* [Bug] [Kling] Fix Kling camera control (#161)
* Kling Image Gen v2 + improve node descriptions for Flux/OpenAI (#160)
* [Kling] Don't return video_id from dual effect video (#162)
* Bump frontend to 1.18.8 (#163)
* Use 3.9 compat syntax (#164)
* Use Python 3.10
* add example env var
* Update templates to 0.1.11
* Bump frontend to 1.18.9
---------
Co-authored-by: Robin Huang <robin.j.huang@gmail.com>
Co-authored-by: Christian Byrne <cbyrne@comfy.org>
Co-authored-by: thot experiment <94414189+thot-experiment@users.noreply.github.com>
* Upload files for Chroma Implementation
* Remove trailing whitespace
* trim more trailing whitespace..oops
* remove unused imports
* Add supported_inference_dtypes
* Set min_length to 0 and remove attention_mask=True
* Set min_length to 1
* get_mdulations added from blepping and minor changes
* Add lora conversion if statement in lora.py
* Update supported_models.py
* update model_base.py
* add uptream commits
* set modelType.FLOW, will cause beta scheduler to work properly
* Adjust memory usage factor and remove unnecessary code
* fix mistake
* reduce code duplication
* remove unused imports
* refactor for upstream sync
* sync chroma-support with upstream via syncbranch patch
* Update sd.py
* Add Chroma as option for the OptimalStepsScheduler node
* Add basic support for videos as types
This PR adds support for VIDEO as first-class types. In order to avoid
unnecessary costs, VIDEO outputs must implement the `VideoInput` ABC,
but their implementation details can vary. Included are two
implementations of this type which can be returned by other nodes:
* `VideoFromFile` - Created with either a path on disk (as a string) or
a `io.BytesIO` containing the contents of a file in a supported format
(like .mp4). This implementation won't actually load the video unless
necessary. It will also avoid re-encoding when saving if possible.
* `VideoFromComponents` - Created from an image tensor and an optional
audio tensor.
Currently, only h264 encoded videos in .mp4 containers are supported for
saving, but the plan is to add additional encodings/containers in the
near future (particularly .webm).
* Add optimization to avoid parsing entire video
* Improve type declarations to reduce warnings
* Make sure bytesIO objects can be read many times
* Fix a potential issue when saving long videos
* Fix incorrect type annotation
* Add a `LoadVideo` node to make testing easier
* Refactor new types out of the base comfy folder
I've created a new `comfy_api` top-level module. The intention is that
anything within this folder would be covered by semver-style versioning
that would allow custom nodes to rely on them not introducing breaking
changes.
* Fix linting issue
* draft pass at a native comfy implementation of Lotus-D depth and normal est
* fix model_sampling kludges
* fix ruff
---------
Co-authored-by: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
This commit relaxes divisibility constraint for single-frame
conditionings. For single frames, the index can be arbitrary, while
multi-frame conditionings (>= 9 frames) must still be aligned to 8
frames.
Co-authored-by: Andrew Kvochko <a.kvochko@lightricks.com>
This patch fixes a bug in LTXVCropGuides when the latent has no
keyframes. Additionally, the first frame is always added as a keyframe.
Co-authored-by: Andrew Kvochko <a.kvochko@lightricks.com>
The frontend part isn't done yet so there is no video preview on the node
or dragging the webm on the interface to load the workflow yet.
This uses a new dependency: PyAV.
* Add 'sigmas' to transformer_options so that downstream code can know about the full scope of current sampling run, fix Hook Keyframes' guarantee_steps=1 inconsistent behavior with sampling split across different Sampling nodes/sampling runs by referencing 'sigmas'
* Cleaned up hooks.py, refactored Hook.should_register and add_hook_patches to use target_dict instead of target so that more information can be provided about the current execution environment if needed
* Refactor WrapperHook into TransformerOptionsHook, as there is no need to separate out Wrappers/Callbacks/Patches into different hook types (all affect transformer_options)
* Refactored HookGroup to also store a dictionary of hooks separated by hook_type, modified necessary code to no longer need to manually separate out hooks by hook_type
* In inner_sample, change "sigmas" to "sampler_sigmas" in transformer_options to not conflict with the "sigmas" that will overwrite "sigmas" in _calc_cond_batch
* Refactored 'registered' to be HookGroup instead of a list of Hooks, made AddModelsHook operational and compliant with should_register result, moved TransformerOptionsHook handling out of ModelPatcher.register_all_hook_patches, support patches in TransformerOptionsHook properly by casting any patches/wrappers/hooks to proper device at sample time
* Made hook clone code sane, made clear ObjectPatchHook and SetInjectionsHook are not yet operational
* Fix performance of hooks when hooks are appended via Cond Pair Set Props nodes by properly caching between positive and negative conds, make hook_patches_backup behave as intended (in the case that something pre-registers WeightHooks on the ModelPatcher instead of registering it at sample time)
* Filter only registered hooks on self.conds in CFGGuider.sample
* Make hook_scope functional for TransformerOptionsHook
* removed 4 whitespace lines to satisfy Ruff,
* Add a get_injections function to ModelPatcher
* Made TransformerOptionsHook contribute to registered hooks properly, added some doc strings and removed a so-far unused variable
* Rename AddModelsHooks to AdditionalModelsHook, rename SetInjectionsHook to InjectionsHook (not yet implemented, but at least getting the naming figured out)
* Clean up a typehint
The 10 step minimum for the AYS scheduler is pointless, it works well at lower steps, like 8 steps, or even 4 steps.
For example with LCM or DMD2.
Example here: https://i.ibb.co/56CSPMj/image.png
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