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ComfyUI-Viggle-Animate-H3
ComfyUI nodes for Viggle-Animate minimax H3 finetune
ComfyUI-HunyuanVideo-Foley
HunyuanVideo-Foley: Multimodal Diffusion with Representation Alignment for High-Fidelity Foley Audio Generation.
Hue and saturation
Create a color-adjusted or single-hue colorized image from an uploaded source image. For a first run, upload your image and run with the saved settings: Master, HSL, Hue 3.9, Saturation 0 and Lightness or brightness 0. This applies a small hue shift. For an unchanged starting preview, set Hue to 0 as well, then change a control and run again. Choose Master to adjust all colors, or Reds, Yellows, Greens, Cyans, Blues or Magentas to target an existing hue range. These ranges are based on pixel color, not objects or manually selected regions, and leave grayscale pixels unchanged. If a mode control appears as a text field, enter the exact choice name. Hue shifts colors by -180 to 180 degrees. Saturation uses a unitless -100 to 100 scale: negative values reduce saturation, positive values increase it, and 0 adds no adjustment. Lightness or brightness also uses -100 to 100: negative darkens, positive brightens, and 0 adds no adjustment. The three adjustments combine in one output. In advanced controls, HSL adjusts saturation and lightness; HSB/HSV adjusts saturation and brightness. Color range overlap feathers individual hue ranges into neighboring colors, with higher values extending the affected range. The saved overlap is 50. Use a value above 0 through 100: exactly 0 makes the shader's feather calculation undefined. Overlap is ignored in Master and Colorize. Choose Colorize for a single-hue treatment using source luminance as the starting lightness. Hue becomes the target hue: 0 is red, 60 yellow, 120 green, ±180 cyan, -120 blue and -60 magenta. Set Saturation above 0 through 100 to add color; 0 produces grayscale, and negative saturation values are clamped to 0. Lightness or brightness adjusts HSL lightness in this mode. Colorize always uses HSL and ignores both Color space and overlap. Strong saturation or tonal adjustments can flatten color or tonal detail. Output dimensions follow the source image. Uploaded transparency is not preserved because the image loader's separate alpha mask is unused. This output applies only hue, saturation and the associated tonal adjustment or Colorize treatment; the other effects in this family are separate tools.
SeedVR2 image upscale: mechanisms and practical controls
Enlarge an image with the exact SeedVR2 3B int8 recipe, understand its image-conditioned restoration path, and choose size, color and tiling settings without assuming pixel or alpha preservation.
Wan 2.2 14B Image to Video (Multiple Lora) Beginner Friendly Workflow Template — v2.0
Functionally it's the same as the last version, I just wanted to adjust the way the workflow looked a bit and color code the important nodes, enjoy!
Ultra photo-realistic workflow | refiner, upscaling, FaceDetailer (+index elements), inpainting, controlnet, Civitai Metadata (NOOBAI-XL/ILLUSTRIOUS/SDXL) ComfyUi — v2.5
STEPS BASE (after this value the refiner kicks in) should never exceed the value of TOTAL STEPS unless you want to use only the first KSampler.
Image upscale and refinement: mechanisms and practical controls
Enlarge an illustration while controlling initial refinement, tile redraw, seam correction and final sharpening in this exact recipe.
Wan 2.2 first–last frame video: mechanisms and practical controls
Configure a silent video from endpoint images and text, understand the shared sampling schedule, and distinguish generation controls from playback and encoding controls.
Seedance first and last frame video
Generate a prompted video transition between two uploaded images, with optional audio on Seedance 1.5 Pro. Both first and last frame images are required. This Pipe sends the images and prompt to ByteDance Seedance through a paid provider call and returns one generated video to Sweet Tea. For a first run, upload both images, replace the capybara example prompt with motion, transformation, and camera instructions suited to them, and keep the default Seedance 1.5 Pro model, 720p resolution, adaptive aspect ratio, and five-second duration. The example describes six shots and six seconds of audio; adapt its scope and timing to your requested clip. Duration sets the requested length from 3 to 12 seconds in whole-second increments. Resolution offers 480p, 720p, and 1080p. Aspect ratio offers adaptive sizing or a fixed frame proportion. Consider both endpoint compositions when choosing a fixed ratio. Model selection offers Seedance 1.5 Pro, 1.0 Pro, and 1.0 Lite. Generate audio is enabled by default and applies only to Seedance 1.5 Pro; describe desired music, sounds, or ambience in the prompt. Other available models ignore that control. Fix camera adds a provider instruction for a stationary camera, but the effect is not guaranteed. Avoid conflicting camera movement instructions when enabling it. Seed -1 requests a new random seed each run; a fixed seed controls generation randomization. Watermark optionally requests an AI-generated label. The image inputs use RGB image data; uploaded transparency is not carried through this workflow. The output is returned through Sweet Tea's video preview transport rather than the original local SaveVideo stage.
Wan 2.6 text to video
Generate a video from an English or Chinese scene description using Wan, with optional generated audio and continuous-shot or multi-shot composition. No uploaded image, video, or audio input is exposed in this Pipe. For a first run, replace the example scene description with your subjects, actions, setting, camera movement, and visual style. Keep Wan 2.6, landscape 720p, and the five-second duration. Audio generation and AI prompt enhancement are enabled by default; include desired sound in your description when using generated audio. Review the negative prompt and replace scene-specific exclusions that do not apply. Output size selects resolution and aspect ratio together. Duration is in seconds: Wan 2.6 supports 5, 10, or 15; when selecting Wan 2.5 preview, choose 5 or 10. Shot type selects one continuous shot or multiple shots with cuts, and takes effect only while Enhance prompt is enabled. Disable enhancement to submit your wording without AI expansion. Turn off Generate audio if you do not want automatic audio generation. Seed -1 randomizes each run; enter a fixed seed to control randomization. Watermark requests an AI-generated watermark and is disabled by default. The generated video is returned to Sweet Tea. In the advanced Video output section, leave file type and codec on auto for the first run, or select an explicit container and encoding. Keep the supplied CRF default unless you need to configure encoding quality.
LTX-2.5 image to video with audio
Animate a starting image into one video with generated audio using LTX-2.5. Upload a first frame and describe the scene, action, camera movement, and desired sounds or dialogue. There is no audio-upload input. For a first run, replace the example prompt to match your image and keep 5 seconds, 24 FPS, 16:9, and 0.9 output megapixels. Use an image with a similar aspect ratio when composition matters. Aspect ratio and megapixels determine output dimensions rounded to a 32-pixel multiple. Initial generation uses half those dimensions, followed by 2× spatial latent upsampling and joint video/audio refinement. Increasing resolution, duration, or FPS increases the work required. Enhance prompt selects a rewrite informed by your text and uploaded image. Turn it off to select your original wording. Enhancement length controls the rewrite's text budget, not video duration. Sample enhanced wording uses on/off choices; temperature, probability filters, penalties, and enhancement seed apply when sampling is on. Thinking mode depends on support from the fixed enhancement model, and Use enhancement template selects its built-in template when available. Text-to-video mode bypasses starting-frame injection in both stages. An image upload remains required because preprocessing stays connected. Also turn off Enhance prompt to make generation conditioning come only from your text. Initial and refinement image strengths are independent and inactive in text-to-video mode. The uploaded alpha mask is not connected; transparency is not preserved as an output feature. Enter positive whole-second duration and a whole frame rate from 1 to 120 FPS. Choose duration × FPS divisible by 8, with duration × FPS + 1 at most 1000. At 24 FPS, whole-second durations from 1 through 41 meet these conditions. The default requests 121 frames, so playback can be about one frame longer than five seconds. Generation, refinement, and sampled prompt enhancement have separate seeds. Use -1 to randomize each run. For comparisons with fixed random inputs, set all applicable seeds explicitly and keep enhancement settings unchanged. Both stages share the negative prompt and expose separate video and audio guidance inputs. Keep guidance at 1 for a first run; supported tuning ranges are not established by the supplied evidence. Advanced settings preserve independent samplers and editable comma-separated noise schedules for both stages, plus source-image compression from 0 to 100. Keep their authored defaults initially. There is no separate Steps control: the manual schedules define sampling transitions. Image compression affects the image used for enhancement and conditioning. Export settings offer automatic or explicit container and codec selection, with 8- or 10-bit video assembly. Keep auto and 8-bit for a first run. The source notes that 10-bit supports smoother gradients but may have more limited compatibility. Export settings affect encoding rather than generation. The retained CRF field stays hidden at -1 because its effective quality behavior is not established by the supplied evidence.
Clip Vit Base Patch32
Disclaimer: The model card is taken and modified from the official CLIP repository, it can be found here.
GPT Image generation and editing
Generate one to eight images from a text prompt, or edit an uploaded reference with GPT Image. Returned images appear together in the Pipe result. For a first run, leave Source image disabled, replace the example prompt with a description of your desired image, and keep the default square size and one image. For editing, enable Source image, upload a reference, and describe the desired changes. The upload supplies two inputs: an RGB reference image and a separate mask derived from its alpha channel. Transparent areas become white mask areas designated for replacement. Uploaded transparency is not retained in the RGB reference. There is no separate mask upload or independent mask control; the same upload supplies both inputs. Choose a model and an Output size preset or automatic sizing. Custom width and height apply only when Output size is Custom and Model is GPT Image 2. Each dimension must be a multiple of 16 from 1024 to 3840 pixels. Image count requests one to eight results. Quality affects provider cost and generation time. Background requests automatic, opaque, or transparent provider output; preservation of generated alpha in the returned Pipe images is not established. The provider backend does not implement seed support, so seeds cannot reproduce earlier results. Runs use the partner API and require its access and credits.
Pixel Anchored Remaster — v1.1
🚀 Version 1.1 Update Notes
Kandinsky 5 text to video: mechanisms and practical controls
Make one silent clip from text and distinguish generation, playback and encoding controls in this exact recipe.
Ideogram 4 image generator: mechanisms and practical controls
Generate a scene image with the fixed Ideogram 4 model pair, and choose canvas, schedule and guidance settings without confusing prompt content with execution controls.
Subject and product composition
Generate a scene featuring a subject and product from two reference images using Gemini. Upload a subject image and a product image. In the scene prompt, image 1 means the subject and image 2 means the product. For a first run, keep the supplied prompt to request the subject holding the product with its logo visible, leave the other defaults in place, and run the Pipe. Edit the prompt to describe the interaction, setting, lighting, style and details to retain. Choose the output aspect ratio and resolution. Auto follows the reference aspect ratio; the product reference is resized and padded to match the subject image dimensions before both images are sent to Gemini. The 2K and 4K settings use Gemini's native upscaler. In Product reference preparation, padding selects white or black borders around the resized product, and interpolation selects its pixel resampling method. These controls affect the reference image rather than the generated scene background or final image size. Model selects either the supplied Gemini Pro image model or Nano Banana 2 (Gemini 3.1 Flash Image). Keep the supplied Generation instructions initially; edit them to change the provider's general behavior alongside the scene prompt. Provider response offers IMAGE or IMAGE+TEXT, but this Pipe returns only generated images through its image preview output; accompanying provider text is not returned. Use seed -1 for a new random seed each run. A fixed seed requests best-effort repeatability but does not guarantee identical results. Subject identity, product details and logo fidelity are requests rather than guarantees. Uploaded alpha masks are not connected, so uploaded transparency is not preserved through the reference path. Both reference images and the generation instructions are sent to Gemini for a provider-priced generation request.
Grok video
Generate one short video using Grok from a text prompt, optionally guided by a starting image. For a first run, describe the scene, subject action and camera movement. Keep grok-imagine-video selected, leave Starting image disabled, and use the default six-second duration and 720p resolution. Run the Pipe to receive the video in Sweet Tea. To use a starting frame, enable Starting image and upload an image. This is optional for grok-imagine-video and required for grok-imagine-video-1.5. Describe how the pictured scene should develop. Selecting grok-imagine-video-1.5 requires a starting image even if your prompt is complete. Only that model supports 1080p; 480p and 720p are also available. Duration sets the video length from 1 to 15 seconds. Aspect ratio controls the video shape; choose a listed ratio or leave auto for automatic selection. Seed controls whether the provider request is rerun, rather than making the generated video reproducible. Leave it at -1 to randomize the rerun value each run; a fixed value does not guarantee identical results. Under Video output, leave File type and Codec at auto for automatic encoding selection, or choose an available format and codec. The output stage returns the video to Sweet Tea rather than saving it through the original SaveVideo node. Generation uses a paid Grok provider call and sends the prompt and any enabled starting image to the provider.
Vidu Q3 image to video: mechanisms and practical controls
Turn one starting image into a Vidu Q3 video. Choose compatible model and resolution settings, align prompt timing with duration, and control sound and seed with the retained limitations in view.
