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花想容/Chinese style/古风/中国風です Lora
推荐的质量词: masterpiece, best quality, score7, score8, highres, extremely detailed 8k, illustration, great quality, amazing quality, very aesthetic, absurdres, Chinese style,
SeedVR2 image upscale
Upscale and restore an uploaded still image with SeedVR2, returning the restored image directly. For a first run, upload an image, leave the target width at 1080 pixels and guidance at 1.01, then run. Compare the result with your original: restoration can reinterpret fine details. The target-width control accepts 1–4320 pixels. The seed defaults to -1 for a fresh random seed each run. Choose a fixed seed from 0 to 5000 when comparing guidance or other settings. Guidance accepts 0.01–2. GPU-memory conservation is enabled by default and can be toggled. Processing batch size defaults to 1; keep that starting value for the single uploaded image. It does not select the number of output variants. The fixed seedvr2_ema_3b_fp16.safetensors model and the SeedVR2 custom node must be available in the runtime. This Pipe accepts still images and has no video input or encoding mode. Uploaded transparency is not preserved because the loader's separate alpha-mask output is not connected.
veryBadImageNegative
veryBadImageNegativev1.3 uses a new training atlas and performs well when used in AOM3 and viewer-mixv1.7 .
Character motion transfer
Animate a reference character using motion poses from a source video, producing one animation assembled from five sequential generated segments. Provide a character reference image and a motion video file path accessible to the execution runtime. The image supplies appearance, reference pose and an automatic caption; the video supplies motion poses. Source audio and uploaded image transparency are not used. For a first run, use a reference showing the character's body clearly and a motion clip with one clearly visible performer. Edit both dancing prompt additions to describe your intended action. They surround the automatic reference-image caption, which remains part of the positive prompt. Keep the default six sampling steps, guidance settings, 81 frames per segment and five-frame overlap. The default output is a silent H.265 MP4. Width and height control both input resizes. The default requested portrait size is 450 by 800 pixels; actual dimensions are adjusted for divisibility by 16. Both inputs use aspect-preserving cropping, with independent reference and motion crop positions. Keep the character and relevant limbs inside each crop. Frame rate is shared between motion-source resampling and final playback. Enter a positive FPS value. Frame stride keeps every nth resampled source frame; values above 1 advance the action faster at the unchanged playback FPS. Skip initial frames selects a later starting action. Source frame limit caps loaded motion frames, with 0 meaning no cap; it does not change the number of generated segments. The graph always generates an initial segment and four continuations rather than automatically matching the full source duration. Keep frames per segment in the 4n+1 pattern, such as 81, and no greater than 256. Keep overlap below the segment length and no greater than 64. Provide enough sampled motion frames for the initial segment. Each continuation defaults to repeating the last available pose when its motion window runs out; its short-source behavior can instead require enough frames by selecting error. Reference strength and its sampling start/end fractions apply across all segments. Body, hand and face pose components can be enabled independently for the motion source and reference image. Pose strength, pose CFG and sampling start/end fractions are independent for each segment. Pose CFG has no effect while the corresponding sampler CFG is 1. The negative prompt is shared, and its influence depends on sampler CFG. Steps is shared by all five samplers. Seeds, CFG, schedule shift, scheduler and denoise are separate per-segment controls. Start with the source defaults and matching segment settings; earlier generated frames become context for later segments, so an early change can affect the remaining video. The fixed Lightx2v distillation LoRA is part of the six-step setup and has an adjustable strength. Advanced continuation context controls adjust the encoded generated-frame multiplier and noise augmentation for each later segment. Automatic caption controls affect the positive prompt used by every segment. Caption seed matters when caption sampling is enabled; the token limit is a ceiling, and lowering it can truncate the caption. Seed -1 requests fresh randomization for the caption or the corresponding video segment. Video output controls change encoding rather than generated motion. File type and codec are selectable; choose compatible combinations supported by the runtime. The source defaults are MP4, H.265, 10-bit yuv420p10le and sRGB. CRF defaults to 22; for codecs using CRF, lower values generally retain more detail and produce larger files. Bitrate is expressed in Mbps, with 0 leaving a positive bitrate unspecified. Keep pixel format and bit depth consistent with the codec. HDR encoding choices do not establish HDR detail in the generated frames.
Wan 2.1 camera-controlled image to video
Animate an uploaded still image into a prompt-guided video with selectable camera movement using Wan 2.1 Fun Camera 1.3B. For a first run, upload a source image, replace the landscape example prompt with a description of your scene and desired subject action, and choose a camera movement. Keep the remaining defaults initially: Zoom In, camera speed 1, 512 × 512 pixels, 81 frames, 16 FPS and generation batch size 1. These settings produce about 5.1 seconds of silent video. The source image supplies starting-frame conditioning and a separate visual reference; its alpha mask is not connected, so transparency is not preserved. Camera choices include Static, directional pans, zooms and clockwise or counterclockwise rotation. Camera speed changes camera conditioning. Width and height use multiples of 16; frame count follows 1, 5, 9 and so on. These shape controls drive both camera and video conditioning. Playback FPS changes duration without changing the generated frame count. Static camera conditioning still permits subject motion described by the prompt. Camera controls condition generation rather than guaranteeing an exact rendered trajectory. In advanced settings, edit the negative prompt to describe unwanted results. Image guidance can be bypassed while keeping the uploaded image connected as the starting frame. Reference crop applies only to image guidance and has no effect when that stage is bypassed. Camera focal-length and optical-center controls are available in Camera and video shape; their source uses a 0–1 scale. Sampling controls include seed, steps, prompt guidance, sampler, scheduler, denoising amount and sampling shift. Seed -1 selects random noise; use a fixed nonnegative seed to reuse the initial noise with the same settings. Denoising amount is not a direct image-preservation slider. The saved sampling settings are 20 steps, CFG 6, uni_pc, simple scheduler, denoising amount 1 and shift 8. Video playback and export expose FPS, 8- or 10-bit depth, container, codec and CRF. Start with automatic container and codec and CRF -1. Some players or downstream tools may not support 10-bit video. Generation batch size controls latent batching, not separate exported files; the selected output assembles decoded images into one video, so use 1 for a single clip. This tool has no connected audio input and returns the video output rather than an animated WebP or individual frame export.
Grok video extension
Continue an existing video with a prompted 2–10 second extension using Grok. For a first run, upload an MP4 clip lasting 2–15 seconds, replace the example space-scene prompt with what should happen next in your footage, and keep the default six-second extension. Describe the action, setting, and camera movement that should follow the clip’s ending. Extension length requests 2–10 seconds in whole-second increments; it does not set the source clip’s length or total output length. The Pipe returns the video supplied by Grok, with no separate concatenation stage. Advanced output encoding controls offer file type, codec, and CRF settings; keep their defaults for a first run. The Grok partner API requires runtime authentication. Leave Seed at -1 for randomization on each run. Seed is a rerun control, and a fixed value does not make Grok’s results reproducible.
Whole-body pose map
Create a rendered whole-body pose map from an image of one person using SDPose. Upload your source image, leave the longer edge at 1024 pixels and all drawing regions enabled, then run to view the output image. The input is resized with its aspect ratio preserved before pose extraction. Choose whether to draw the body, hands, face, feet and head. Head drawing is separate from facial keypoints. Line width changes the skeleton's thickness; face point size applies when Draw face is enabled. The confidence threshold ranges from 0 to 1: raising it omits less-confident keypoints, while lowering it can display more uncertain detections. These controls affect the rendered map rather than pose extraction. Longer edge sets the resized image's longer dimension in pixels; use a positive value. Resampling method selects interpolation before detection. Area is suited to downscaling and Lanczos to upscaling. Advanced settings expose the extractor's processing batch size, defaulting to 16; this does not request multiple output variations. This tool uses the fixed sdpose_wholebody_fp16.safetensors checkpoint and returns a pose visualization through the image preview output, without a separate keypoint-data output. The extractor requires bounding boxes for multi-person detection, and this workflow supplies none, so use a single-person image.
Gemini Omni Flash text to video
Generate a 3–10 second video with audio using Google's Gemini Omni Flash model. The source node specifies 720p output at 24 FPS. For a first run, keep the example video prompt, portrait aspect ratio (9:16), three-second duration and default advanced settings, then run the Pipe. No image, video or audio upload is required. To create your own clip, describe the scene, action, visual style, camera movement and desired sound. Use 9:16 for portrait or 16:9 for landscape. Enter duration as 3s through 10s in whole-second increments. These controls append instructions to the scene prompt rather than cropping or trimming the result; avoid conflicting duration or framing instructions in your prompt. Advanced generation settings expose temperature and top-p sampling controls. Seed -1 randomizes the request seed each run. Seed affects whether the generation node reruns, but results remain non-deterministic even when a seed is repeated. Advanced video output settings expose file type, codec and CRF for output transport. Keep their defaults for the first run; these settings do not change the generation model or scene instructions. Generation requires access to the ComfyUI partner API. The workflow sends the assembled prompt to the Gemini provider and makes a provider-priced generation call. This Pipe uses text input only and returns the generated video; the model's separate text output is not selected.
Wan image to video
Animate an uploaded image into one video using Wan 2.5 or Wan 2.6, with optional generated audio. Upload the image you want to animate and replace the example prompt with instructions matching its subjects and setting. Describe the scene, subject motion, and camera movement in English or Chinese. For a first run, keep Wan 2.5, 720P, and 5 seconds. The result appears in Sweet Tea's video output. Choose 480P, 720P, or 1080P and a duration of 5, 10, or 15 seconds. A 15-second video requires Wan 2.6. The negative prompt describes elements to avoid and may be left blank. AI prompt extension is enabled by default and lets the provider enhance your instructions; disable it to submit your wording without that enhancement. Generated audio is enabled by default and can be turned off. This Pipe has no uploaded audio input. Watermarking is optional and disabled by default. Use seed -1 to randomize each run, or enter a fixed generation seed; identical provider results are not guaranteed. Advanced video output controls select the file type and codec. Leave both on auto for the first run and choose compatible settings when changing them. Uploaded transparency is not preserved: only the loader's RGB image output feeds generation. Generation sends the image and prompt to the Wan API and uses a provider-priced generation call.
Bernini-R: Video Edit
Generate an edited video with consistent relighting using Bernini-R. Ideal for portrait and product relighting, e-commerce catalog photography, and creating consistent lighting across photo sets.
Kling reference image to video
Generate one video from a reference image and a motion prompt. Upload one image, then replace the example prompt with the desired action, scene and camera movement. For a first run, keep kling-v3-omni, five seconds, 16:9 framing and 720p resolution. Generated audio is enabled by default. Choose landscape (16:9), portrait (9:16) or square (1:1) framing, a duration from 3 to 15 seconds, and 720p, 1080p or 4k resolution. The Model control also offers kling-video-o1; turn Generate audio off when selecting it because generated audio is supported only by kling-v3-omni. Execution uses the ComfyUI partner API, sends the reference image and prompt to Kling, and incurs provider charges. Model, duration, resolution and audio choices affect the charge. The image guides the subject and appearance; this Pipe has no separate first-frame or end-frame input. Include desired content and things to avoid in the same prompt. Storyboard mode remains disabled because this interface has no editable segment prompts or durations. Seed defaults to -1 for randomization. It controls provider re-execution rather than reproducibility: results remain non-deterministic with a fixed seed. The Pipe returns one video for preview. Advanced Video output settings provide file type and codec choices, both defaulting to automatic selection.
【FLUX】IMG to IMG — v6.2
A few modifications to standardize my workflows.
Flux 1.1 Pro Ultra image generator
Create a single image with Flux 1.1 Pro Ultra. For a first run, edit the prompt, choose an aspect ratio, and leave reference image guidance disabled. The default produces a square image without an uploaded input. To guide generation with an existing image, enable Reference image and upload an image. Reference strength controls its influence: higher values make the result closer to the reference. This setting has no effect while Reference image is disabled. Enable Raw mode for less processed, more natural-looking images. Prompt expansion lets the provider modify the prompt for more creative generation; with it enabled, the same seed will not produce exactly the same result. Seed defaults to a new random value each run. This workflow uses a hosted API node and requires configured API access and sufficient credits. Output size is controlled by aspect ratio; the source does not expose explicit pixel dimensions.
Boogu image edit
Create edited images from one uploaded reference and a natural language instruction. Upload your source image, enter the change you want and run with the defaults: 1 megapixel, one variant, 25 steps and instruction guidance (CFG) 3.5. “Remove the hat” is an example instruction; choose wording appropriate to your image. The negative prompt can describe unwanted details, or remain empty. Output size sets a target pixel budget in millions while retaining the source aspect ratio. Bypass Output size to derive dimensions from the source image instead. This stage controls output dimensions; the original upload still feeds editing conditioning. Resampling method affects only the image used to derive dimensions. Variants sets the number of edited images returned in a batch. Larger dimensions and batches require more memory. Advanced controls include guidance, seed, sampling steps, sampler and scheduler. Seed -1 selects fresh randomness each run; use a fixed seed when comparing settings with Add noise enabled. Leave Add noise enabled and Noise schedule fraction at 1 for a first run. The workflow starts from an empty latent conditioned on your image and instruction, so lowering the schedule fraction does not directly preserve source pixels. Schedule adjustment changes the sampling configuration used to calculate noise levels; the sampler itself receives the original model. This is a generative editor without a connected editing mask. Instructions to retain details do not guarantee that all other content stays unchanged. Uploaded transparency is not retained because only LoadImage’s IMAGE output is connected. The fixed model files are boogu_image_edit_fp8_scaled.safetensors, qwen3vl_8b_fp8_scaled.safetensors and ae.safetensors. Supplied dependency evidence marks all three model files and the Sweet Tea output node pack as missing in the inspected environment; their source locations are supplied. The selected result is the decoded edited-image batch returned through Sweet Tea’s image output.
Gender Slider
Don't let the Model or Lora push a gender on you. Male, female, and every point in between. You decide. This isn't to push any agenda, just giving you the tools to get the image you want, despite the biases that...
Bad-Hands-5
Check my EXCLUSIVE models on Mage.Space : AniMage PXL • AniReal PXL • Lucid Dream • AniMage SD1.5 • Realistic Portrait SDXL - Pony : AniVerse PXL • AniMerge PXL • AniToon PXL • AniMics PXL • AniVerse XL SD1.5 :...
Bridal Style
This is a Style which brings out a beautiful bridal aesthetic. Simply call Style-Bridal in your prompt and your female characters will be ready for their wedding day!
