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Topaz creative upscale
Create a creatively enhanced, resized image with Topaz Reimagine. Upload a source image and choose Scale factor. For a first run, use the default 4× scale, leave Prompt empty and keep Creativity at 2. A 4× scale requests four times the source width and height, approximately 16 times as many pixels; a scale of 1 requests the original dimensions. Add an optional prompt to guide the desired details or appearance. Creativity accepts values from 1 to 9. Preserve colors enables preservation of the original palette. Subject detection offers All, Foreground and Background modes. For portraits, enable Enhance faces to use Face creativity and Face sharpness, both ranging from 0 to 1. Face sharpness controls how sharp enhanced faces are relative to the background. Preserve facial identity is a separate option and defaults to off. Output dimensions follow the source aspect ratio, subject to pixel rounding; independent width and height choices are unavailable. The size calculation branch supplies dimensions, while the original image goes directly to Topaz. Crop to fill remains off because this workflow has no independent aspect-ratio choice. Uploaded transparency is not preserved: only the loader's image output is connected, without its alpha mask.
Wan 2.1 video inpainting
Generate an edited video segment with SAM3 object selection and Wan 2.1 VACE masked video conditioning. For a first run, upload a source video, replace Object to edit with a description of existing content in that clip, and replace Edit prompt with the desired replacement, scene and motion. Leave Reference image disabled for text-only editing. To add appearance guidance, enable that stage and upload an image. Start frame is a zero-based source-frame index. Frame count requests the segment to edit, and the actual selected frame batch determines generation length. Begin with Start frame 0 and the default 81 frames when the clip has enough frames. Approximate segment duration is frame count divided by the source frame rate. This tool outputs the generated segment, without reinserting it into the full source video. Output width and height are in pixels and are rounded down to multiples of 16. Use positive dimensions of at least 16. Center framing crops while preserving proportions; Disabled stretches to fit. SAM3 selects content after resizing. Mask margin expands that selection in resized-frame pixels; negative margins shrink it. Detection threshold and refinement passes adjust selection. Combined masks are the normal video setting; separate object masks have no dedicated alignment stage here. Fast sampling selects the fixed CausVid LoRA and the Fast steps and Fast CFG controls. Turning it off selects the base model and Standard steps and Standard CFG. CausVid LoRA strength affects only fast mode. Both modes share the seed, sampler, scheduler, denoise strength and sampling shift. Use seed -1 for randomization. VACE control strength is separate from prompt guidance. Keep batch size 1 for the normal single-sequence output; larger batches are not split into separate video outputs. The output uses the source video's frame rate and passes through its audio. Audio is not explicitly trimmed or offset to match Start frame and Frame count, so synchronization and duration may differ for a selected segment. Generated frames are decoded directly, without a final composite that guarantees unchanged pixels outside the mask. Video encoding controls select the output container, codec and compression setting. The workflow uses fixed SAM3, Wan VACE, text-encoder and VAE models; fast mode additionally uses the fixed CausVid LoRA. These model assets must be available to the execution environment. The supplied dependency evidence marks them missing; this review establishes the connected tool and its guidance, not a completed runtime test.
CyberRealistic Negative - Pony v1.0
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Bernini-R image editing
Edit an uploaded image with text instructions using Bernini-R. Upload a source image, describe the changes in English and state what should remain unchanged. For a first run, use “make it night,” a 1280-pixel long edge, Turbo enabled, batch size 1 and frame count 1. Run the Pipe to receive an edited image. The resized source supplies the output dimensions and retains the source aspect ratio. Turbo selects the LightX2V LoRAs and defaults to 6 total steps, a 3-step high-noise stage and CFG 1. Turning it off uses the same Bernini model pair without those LoRAs and defaults to 40 total steps, a 20-step high-noise stage and CFG 5. Each mode has separate advanced step, split and guidance controls; changing controls for the inactive mode does not affect the current run. LoRA strengths apply only with Turbo enabled. Use total steps from 1 to 10000, a positive split strictly below the corresponding total, and CFG from 0 to 100. The negative prompt describes unwanted characteristics. The supplied Chinese text includes artifacts, malformed anatomy and motion-related exclusions; revise it for your intended result. The sampler and noise schedule are shared by both stages. Denoise changes the schedule range rather than directly blending the source and output. Initial-stage noise is enabled by default; its seed uses -1 for a new random seed each run. Set a fixed seed to compare settings. Finishing-stage noise is disabled by default so the second stage continues the existing latent; enabling it makes the separate finishing seed active. Batch size requests multiple results. Frame count 1 produces still images; 5, 9 and subsequent increments of 4 request sequences conditioned on the uploaded still. Results are returned as individual images through the preview output, without video encoding or a playback rate. Prompt prefix offers Default, Text to Image, Text to Video, Image Editing and Subject to Image. These choices only select system prompt wording. The uploaded image remains connected in every selection; reference-image composition and text-only generation are not supported by this selector. The graph uses rendering without a separate prompt planner. Uploaded transparency is not preserved because only the loader’s RGB IMAGE output is connected.
LTX 2.3 first-to-last frame transition
Generate a video transition guided by two uploaded images, with jointly generated audio. Upload both a start image and an end image, then replace the example prompt with your subject, scene, movement, camera motion and transformation. Describe desired sounds or dialogue in the same prompt. The result is one video containing generated audio; there is no audio upload input. Endpoint images guide generation rather than guaranteeing exact copies, and exact dialogue or synchronization is not guaranteed. For a first run, use images with similar framing and keep 720 × 1280 pixels, a requested duration of 6 whole seconds, 25 FPS, both image strengths at 0.7, transition LoRA strength at 1 and CFG at 1. The example prompt describes photography changing into watercolor and includes zhuanchang, the token suggested by the source notes for the transition LoRA. Replace its scene description to match your images. Width and height feed both image resizers; the resized start image establishes the video dimensions. Use explicit positive integer dimensions of at least 64 pixels. Avoid 0: it calculates aspect ratio independently for each image and can produce incompatible guide sizes. Both images are center-cropped by default. Advanced framing controls independently choose center cropping or stretching and interpolation for each image. Area interpolation suits downscaling, lanczos suits upscaling and nearest-exact suits pixel art. Uploaded transparency is not preserved because only the loaders' RGB image outputs are connected. Advanced preprocessing controls independently set compression for each resized image on a 0–100 scale; both default to 25. Duration is requested in positive whole seconds. The graph requests Duration × FPS + 1 frames and shares FPS across audio timing, video conditioning and playback. Use FPS from 1 to 120 and keep Duration × FPS + 1 at or below 1000, the supplied audio latent limit. The extra frame and model frame handling mean requested duration is not an exact final running time. Start and end guide indices default to 0 and -1. Keep these for endpoint guidance, or change them to move the guides within the clip. Negative indices count backward from the end; choose positions within the generated clip. Their strengths independently control image influence. The transition LoRA can be bypassed or set to strength 0 while retaining both image guides. Seed -1 requests a fresh random seed each run; use a fixed nonnegative seed when comparing settings. CFG defaults to 1, where conventional negative-prompt guidance has no effect. If you raise CFG, review the negative prompt first: its supplied exclusions include scene-specific details and restrictions that may conflict with stylized imagery or your intended audio. Advanced sampling controls expose ancestral noise and its noise scale. Ancestral noise defaults to off at 0; noise scale becomes relevant when ancestral noise is nonzero. The manual sigma schedule contains nine values defining eight sampling intervals, with no separate Steps control. Keep the supplied schedule for a first run. Video bit depth defaults to 8-bit. The supported 10-bit option can retain smoother gradients, but some players or downstream tools may not support it. Advanced video file controls offer automatic or explicit container and codec choices. Keep both on auto for a first run; explicit choices must be compatible.
PA7_Portrait_Tools
Portrait promptography is an art form that goes beyond simply capturing someone's physical appearance. It delves deep into the core of their being, aiming to encapsulate their essence, personality, and emotions in a...
LTX-2.3 Audio-Conditioned Video
Create one audio-conditioned video with LTX-2.3. Upload a reference image and audio track, then replace the cactus example prompt with your subject, action, setting and camera movement. For a first run, keep 1280 × 720, 24 FPS, 9 seconds and the supplied sampling settings. Supply enough audio after Audio start to cover Duration. Audio start is measured in seconds; negative values count from the end of the track. Duration controls both audio trimming and video frame calculation: integer(Duration × FPS + 1). The extra frame can make video playback slightly longer than the audio excerpt. Use positive dimensions, duration and frame rate. The source latent layout declares spatial steps of 32 pixels at the initial half resolution and a temporal step of 8 frames; use compatible settings when changing output shape or timing. The workflow generates at half the requested dimensions, upscales the video latent by 2× and runs a refinement pass. Width and height also set reference framing: center crops to the requested aspect ratio, while disabled stretches the image. Reference longer edge independently resizes the prepared image before compression and both image-conditioning passes; its default is 1536 pixels. Uploaded transparency is not used as an alpha mask: only the image loader's RGB image output is connected. Image strength controls reference influence in initial generation; Refinement image strength independently controls its reapplication after upscaling. Text-to-video mode disables image conditioning in both passes while retaining audio conditioning. A valid reference image remains required because its loader and preparation stages stay connected. Enhance prompt is enabled by default and rewrites your scene prompt using text only. Describe relevant image and audio context yourself. Disable it to use your original prompt directly. Advanced prompt settings include text sampling, its independent seed and temperature, token-selection controls, the generation limit, template and optional model-supported thinking mode. The fixed Gemma LoRA strength applies to prompt enhancement separately from the video distillation strength. Initial generation and refinement have independent seeds, CFG, samplers and manual noise schedules. Schedule entries determine sampling intervals; there is no separate Steps control. Keep the supplied schedules and distillation strength for a first run. Seed -1 randomizes each run; fix both video seeds and the sampled enhancement seed, or disable enhancement, when controlling those sources of variation. At CFG 1, the negative prompt has no classifier-free guidance effect in that pass. The delivered video includes audio decoded from the audio latent after both passes, rather than a direct copy of the uploaded file. Exact waveform preservation and precise lip synchronization are not guaranteed. Advanced output settings select container, codec, encoding quality and bit depth; keep their defaults for a first run. Ten-bit video requires compatible encoding and playback.
AloeVera's SuperNegative embeddings
0.VERY IMPORTANT -> All the versions of the embeddings are available on the huggingface link. (Civitai has upload limitations). Also click on "Show more" down below for all the examples/comparisons + tips. ☺️
Runway image generation
Generate images with Runway from a text prompt and an optional reference image. For a first run, replace the example prompt with your desired subject, setting, composition, and visual style. Keep Output shape at 1024:1024 for a square image. Reference image is enabled initially: upload one image, or bypass that stage to generate from text alone. Run to preview the generated result in Sweet Tea. With a reference image enabled, describe the result you want that image to guide. Only one reference image is accepted, and no image transformation strength control is exposed. Other output shape values must be supported by the Runway node; the draft does not enumerate them. Running requires configured ComfyUI partner API access and sufficient account credits. Generation sends the prompt and any enabled reference image to Runway and uses a paid provider call. The output stage returns images for preview without permanently saving them through ComfyUI.
CyberRealistic Negative - Pony v2.0
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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,
