沐阳 H3 · 二采放大设置
The standalone master switch for the long-video second pass
- 二采模型
- 二采设置
H3's first pass is fast and often a bit soft. The second pass is the fix - upscale, redraw at low denoise, keep the audio. 沐阳 H3 · 二采放大设置 (H3DetailSettings) is the standalone control panel for that second pass when you're using 沐阳 H3 · 长视频. It exists because a long-video node can't realistically hold twenty upscaling widgets in its own body without becoming unusable - so the settings live in their own node, and H3LongVideo exposes a single socket that takes the whole bundle.
The output is a single 二采设置 (MYANG_H3_DETAIL) value - a settings dict, not an image. Wire it into H3LongVideo's 二采设置 input, and the long-video loop applies it one segment at a time. Disable it and the long video just runs first-pass only.
The inputs that matter
- enabled - the master switch. Off by default; nothing else matters until this is on.
- mode -
放大 + 二采(upscale then refine, the default and recommended), second pass at the same resolution, or upscale-only with no second pass. - upscale_method - the big choice.
neural_3d(neural 3D latent upscale, marked recommended), pixel/VAE, latent, or NVIDIA RTX VSR. The neural 3D path needs the LBH-123-AI H3 Latent Upscaler weights inComfyUI/models/latent_upscale_models/- download them separately. - resolution / width / height - the output target; custom width/height only apply when you pick 自定义 for the output short edge.
- steps (4 recommended) and denoise (0.2 recommended, keep it 0.15–0.25) - the redraw contract. Low denoise = the upscale decides the look, the model just cleans it up.
- scheduler / sampler_name -
beta/res_multistepdefaults. Note this is deliberately not the Turbo contract - the second pass runs on the base model. - latent_precision -
fp16(recommended, memory-cheap); switch tofp32if you see odd color blocks. - latent_chunk_steps - temporal chunking for the neural 3D upscaler: 8 to save memory, 16 default, 32 faster.
- passes - how many refine rounds; only the first pass upscales, later rounds refine at the same resolution.
- seed_mode - reuse the same seed every round (default) or not.
- 二采模型 (optional) - the Ref2VA base model, before the Turbo LoRA. Required whenever the second pass is enabled - the second pass must not run through a Turbo LoRA.
Install and ground rules
Pack install: ComfyUI Manager search "ComfyUI-MiniMaxH3-Myang", or git clone https://github.com/civilcoco/ComfyUI-MiniMaxH3-Myang into custom_nodes, restart. No extra Python deps. The neural-3D weights and the RTX VSR path (separate NVIDIA VFX runtime) are the only extra downloads, and they're optional.
Final audio always comes from the first pass - the second pass only gets seam handling and duration trimming, which is a deliberate choice to keep the soundtrack untouched. Two practical notes: start the neural 3D path at fp16 / chunk 16, dropping the chunk to 8 if memory bites; and if the first pass is already at your target resolution, mode "second pass at same resolution" exists precisely so you're not upscaling just to redraw. And H3's weights themselves remain territory-restricted (US/EU/UK/South Korea excluded) - the pack can't fix that, so check before you commit.
Inputs (23)
| Name | Type | Default | Description |
|---|---|---|---|
| enabled | BOOLEAN | false | — |
| mode | COMBO | 放大 + 二采(推荐) | 3 options: 放大 + 二采(推荐), 同分辨率二采(不放大), 仅放大(不二采·最快) |
| resolution | COMBO | 832P | 9 options: 540P, 640P, 720P, 768P, 832P, 928P, +3 |
| width | INT | 166432–8192 | 仅在二采输出短边选『自定义』时使用 |
| height | INT | 92832–8192 | 仅在二采输出短边选『自定义』时使用 |
| steps | INT | 41–100 | 二采采样步数(推荐 4 步) |
| denoise | FLOAT | 0.200.01–1 | 二采重绘幅度(推荐 0.15~0.25) |
| scheduler | COMBO | beta | 3 options: beta, simple, normal |
| sampler_name | COMBO | res_multistep | 2 options: res_multistep, euler |
| upscale_method | COMBO | neural_3d (神经3D Latent放大·推荐) | 3 options: neural_3d (神经3D Latent放大·推荐), pixel (像素放大·自用版工作流方式), nvidia_rtx_vsr (NVIDIA RTX 视频超分·实验) |
| chunk_frames | INT | 41–64 | 放大分组帧数;RTX VSR 内部仍逐帧进出显卡 |
| latent_upscale_model | COMBO | 神经3D模式的 Apache-2.0 权重;放到 models/latent_upscale_models | |
| latent_precision | COMBO | fp16(推荐·省显存) | fp16 更省显存;出现异常色块时改 fp32 |
| latent_chunk_steps | INT | 00–256 | 神经3D时间分块;0=全上下文单次推理(无接缝,推荐)。显存不够再往上调,8 最省显存 |
| passes | INT | 11–8 | 二采轮数;只在前一轮放大,后续保持同分辨率精修 |
| seed_mode | COMBO | 每轮沿用同一种子 | 2 options: 每轮沿用同一种子, 每轮种子 +1 |
| reuse_condition | BOOLEAN | true | 开:只复用文本token与已编码参考素材,不包含、不复制一采成片;二采目标latent始终独立。关:按二采分辨率重跑一次条件,参考图会被重采样到更大面积,token 全变,低降噪几步收不过去,容易涂抹和轻微身份漂移 |
| memory_profile | COMBO | 自动平衡(16GB推荐) | 控制二采模型权重驻留与激活空间,以及清晰逐步预览频率;DynamicVRAM下激活空间仍会被计算使用,不是空置预留。不改变832P输出、步数、重绘幅度或最终画质 |
| custom_reserve_gb | FLOAT | 1.250–8 | 仅自定义档生效;DynamicVRAM下为二采激活空间,非动态模式下为传统显存预留;0=沿用ComfyUI启动设置 |
| custom_preview_interval | INT | 20–100 | 仅自定义档生效;0=关闭二采逐步清晰预览,1=每步,2=每2步。二采完成后的最终预览始终保留 |
| continuous_sigma | BOOLEAN | false | 开启后把一采步数和二采步数组成一条 Sigma 轨迹:低分辨率执行前半段,放大 noisy latent 后继续剩余步数。将复用一采模型、采样器、调度器与种子;不增加总步数,但暂不兼容音频精修、小脸/动作修复、检查点直入和像素放大。 |
| vsr_enhance | BOOLEAN | false | 仅『同分辨率二采』生效:解码后按原尺寸跑一遍 NVIDIA RTX VSR,只去噪锐化,不改分辨率。需要 nvvfx 与 NVIDIA 显卡;每段一次隔离进程加一整段磁盘往返、逐帧推理。『放大 + 二采』和『仅放大』请用放大方式里的 VSR,否则同一批帧要过两遍 |
| 二采模型opt | MODEL | 接 Turbo LoRA 之前的 Ref2VA 基模;开启二采时必须连接 |
Outputs (1)
| Name | Type | Description |
|---|---|---|
| 二采设置 | MYANG_H3_DETAIL | — |