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djz CYBER KAN V0
Curated Collection of Manga Illustrations from my videogame series "BIG KAN", part of the Paradise Universe.
Handsome male models' face (18-30) /realism/
if you want more stronger changes and push the images towards more 18-20 years face, use it around 1.5-2.00
Restyle an image with Seedream 5.0 Lite
Restyle a source image using a second image as a visual reference and a written instruction. Upload both required images: the picture to change as Source image and an example of the desired look as Style reference. In Edit instruction, refer to them as the first and second images respectively. The default instruction requests style transfer; edit it to describe the changes you want and the details to preserve. For a first run, keep the square 2048 × 2048 preset and Maximum images at 1, then run the tool to view the generated image. Select Custom under Output size to activate Width and Height, measured in pixels. Width accepts even values from 1024 to 6240; Height accepts even values from 1024 to 4992. Maximum images at 1 produces one result. Higher values request between one and the chosen maximum number of related images; describe the desired variations in the instruction. With these two reference inputs, use at most 13 generated images because input and generated images together cannot exceed 15. Enable Require complete results to abort on missing or errored requested images; the default accepts available results. Seed -1 randomizes each run; enter a fixed seed to control the generation seed. AI watermark asks the provider to add an AI-generated watermark. Prompt reasoning stays enabled because it cannot be disabled when reference images are supplied. This tool uses the Seedream provider API, sends the reference images and instruction to the provider, and requires configured provider access with provider billing. Generated images are returned through the preview output. Uploaded alpha masks are not connected, so transparency preservation is not supported.
negative_hand Negative Embedding
Currently, there are more and more negative embedding, while many are also very good and easy to use. However, almost all of them currently have a big problem... They change the main or initial artstyle of the used...
Two-speaker dialogue
Enter each speaker's dialogue and choose a voice for each entry. ElevenLabs generates the entries together, and the result is saved as MP3. Stability controls emotional variation versus consistency. Leave the language code empty for automatic detection. Voice cloning is not connected to this output.
Reference-guided relighting
Generate one relit image from a subject image and a lighting reference, or from the subject and text instructions alone. For a first run, upload the subject as image 1 and a lighting reference as image 2. Keep the lighting-reference stage enabled, retain the supplied prompt, and leave Lightning mode off. The supplied Chinese prompt asks to remove image 1's original lighting and relight it using image 2's lighting and color tone. Standard sampling uses 20 steps and CFG 4. Enable Lightning mode to select the additional 4-step Lightning LoRA and its separate settings, initially 4 steps and CFG 1. Switching modes selects the current values for that mode; it does not reset edited values. Each mode's steps and CFG remain independently adjustable. Lightning mode uses the 4-step model artifact, even if an upstream source note mentions an 8-step artifact. The light-migration LoRA remains active in both modes. To relight without a reference, disable the lighting-reference stage and rewrite the instructions to describe the desired lighting directly, without referring to image 2. No reference upload is needed in this mode. A subject upload is always required; when the reference stage is enabled, upload a reference too. Advanced controls include an optional negative prompt, both LoRA strengths, denoise, seed, sampler, scheduler, guidance normalization and sampling shift. Lower denoise retains more of the initial subject's structure and can limit the lighting change. Use seed -1 for a fresh random seed, or a fixed seed to compare edits with the same initial noise. LoRA strengths control their model contributions; Lightning strength only affects Lightning mode. Changing an inactive mode's steps or CFG affects subsequent runs in that mode. The subject is automatically scaled before conditioning and sampling, with no independent output-size control. The Pipe returns one generated image. Relighting may change subject details, and uploaded transparency is not preserved because only the image loaders' RGB outputs are connected.
Grok image edit
Create one or more Grok-edited images from an uploaded source image and text instructions. For a first run, upload the image you want to edit, replace the robot example prompt with your own instructions, and use the default grok-imagine-image model, 1K resolution, and one result. Describe both the changes you want and any details or framing you want retained, then run the tool. Choose among grok-imagine-image, grok-imagine-image-quality, and grok-imagine-image-pro. Resolution offers the provider's 1K or 2K setting rather than an exact width and height. Request 1–10 edited results from the same source image and instructions; this does not add source images. Aspect ratio stays automatic because the provider's explicit aspect-ratio setting requires multiple source images, while this tool supplies one. Seed controls whether the provider node re-runs; results remain nondeterministic even when a seed is repeated. Leave it at -1 to randomize the re-run seed each run. Uploaded transparency is not preserved: only the loader's RGB image output reaches the editor.
Magnific portrait skin enhancement
Produce a skin-enhanced portrait using Magnific's creative mode. Upload a portrait, leave sharpening at 0 and smart grain at 15 for your first run, then run the Pipe to receive the enhanced image. Sharpening controls sharpening intensity; smart grain controls grain intensity. Both use a 0–100 scale and can be adjusted independently. Creative mode allows artistic changes to the portrait's appearance. This Pipe supports creative mode only; faithful and flexible modes are unavailable. Uploaded transparency is not preserved because processing uses the loader's RGB image output. Processing sends the portrait to the Magnific partner API, requires provider authentication configured in the runtime, and uses provider-priced processing.
Seedance 2.0 text to video
Generate one video from a scene description, with optional generated audio. No uploaded media is required. For a first run, use the supplied five-second fantasy prompt with Seedance 2.0, 720p, 16:9 and Generate audio enabled. Alternatively, replace the prompt with your subject, setting, action, visual style and camera movement. Include desired sound when audio is enabled. This workflow calls the ByteDance provider API, requires runtime authentication and uses provider-priced generation. Choose Seedance 2.0, Seedance 2.0 Fast or Seedance 2.0 Mini. Resolution is a text field: enter a value supported by the selected model rather than assuming every resolution works with every model. Aspect ratio sets the frame shape; adaptive leaves that choice to the provider. Duration accepts 4–15 seconds. When changing it, update any duration or shot timestamps in the prompt as well. Prompt wording such as '8K' does not replace the Resolution control. Disable Generate audio for a silent result. Watermark requests a provider watermark. Seed defaults to -1 for randomization on each run. A fixed seed does not reproduce the same video; the source describes generation as non-deterministic regardless of seed. The generated video is returned as one preview result. Under advanced Video encoding, leave File type and Codec at auto for automatic selection, or choose a supported container and compatible codec. This output uses Sweet Tea's preview transport rather than the original SaveVideo stage.
fal.ai LTX Video
Describe a scene and its motion to generate a video through fal.ai's LTX Video 13B Distilled endpoint. This workflow accepts text only and returns the generated video. For a first run, enter a prompt describing the subject, setting, action, and camera movement. Keep the source defaults of 480p, 16:9, and 121 frames. The negative prompt provides a starting list of visual and motion defects to discourage. Resolution and aspect ratio set the video shape. Frame count sets its length in frames; this workflow does not expose FPS, so frame count is not a duration in seconds. Frame count must be entered as an integer, without units. Alternative shape values and frame counts must be supported by the provider. Seed defaults to randomization on each run. A fixed seed is available for exploring variations under otherwise similar settings, without a guarantee of identical provider results. Generation requires configured fal.ai access.
Seedance text to video
Generate one short video from a scene description with Seedance, with optional generated audio on Seedance 1.5 Pro. No uploaded media is required. For a first run, keep Seedance 1.5 Pro selected and use the example prompt or describe your own subject, setting, action, and camera movement. The defaults request a five-second, 720p, widescreen video with generated audio. Include dialogue or sound intent in the prompt when audio is enabled, and keep the action and dialogue appropriate for the chosen duration. Choose a duration from 3–12 seconds, a resolution of 480p, 720p, or 1080p, and the aspect ratio for your intended frame shape. Model lets you select the listed Seedance 1.0 alternatives; those models ignore Generate audio. With Seedance 1.5 Pro, turn Generate audio off for a silent result. Fixed camera adds a stationary-camera instruction to the prompt but does not guarantee camera lock. Remove conflicting camera movement instructions when enabling it. AI watermark requests an “AI generated” watermark. Seed -1 randomizes each run; a nonnegative seed controls the generation's random input. The generated video is returned through Sweet Tea's video output transport with automatic format and codec selection by default. Generation sends your prompt to the ByteDance provider and uses provider-priced billing.
Wan 2.1 VACE text to video
Generate a silent video from text using Wan 2.1 VACE 14B. For a first run, replace the supplied car-scene prompt with your subject, setting, visual style and intended motion. Keep the remaining defaults: 1280 × 720 pixels, 81 frames, 16 FPS, batch size 1, CausVid enabled, 4 sampling steps and CFG 1. The output lasts about 5.1 seconds. No media upload is required. Width and height use multiples of 16. Frame count advances by four from 1. Frame count determines how many frames are generated; FPS changes playback speed and duration without adding frames. Keep batch size 1 for a single sequence: this Pipe assembles one video output and does not offer separate files per batch item. The advanced negative prompt discourages unwanted traits; its supplied Chinese text includes static frames, blur, overexposure, text overlays and visual artifacts. CausVid uses a fixed LoRA with separate model and text-encoder strengths. The supplied guidance recommends testing model strength between 0.3 and 0.7 if motion is shaky or blurry. To use the base-model mode, bypass CausVid and manually set Sampling steps to 20 and CFG to 6. Bypassing does not update these settings automatically. Use seed -1 for randomization or a fixed nonnegative seed to reuse starting noise. Sampler, scheduler, denoising amount and schedule shift remain available for advanced adjustment; keep their supplied defaults for a first run. Video playback includes an 8- or 10-bit choice; 10-bit may reduce gradient banding but is not supported by every player or downstream node. Video export provides container, codec and CRF controls. Keep automatic container and codec selection and CRF -1 for the first run; these settings affect encoding rather than generated content. This is a text-only configuration: no reference image, control video, control mask or audio is connected. The VACE strength field does not add those inputs. The model and CausVid LoRA are fixed; smaller-model alternatives and animated WebP export are not selectable modes in this Pipe.
