Eric Qwen-Image UltraGen (ControlNet)

A ComfyUI node in Eric Qwen-Image with 34 inputs and 1 output.

By EricRollei·Created 5 months ago·Updated 3 months ago· 19

pipeline
controlnet
control_image
upscale_vae

image

◄cn_fit_modematch_control►

◄prompt—►

◄negative_prompt低分辨率，低画质，肢体畸形，手指畸形，画面过饱和，蜡像感，人脸无细节，过度光滑，画面具有AI感。构图混乱。文字模糊，扭曲。►

◄aspect_ratio1:1 Square►

◄seed0►

◄seed_modeoffset_per_stage►

◄max_sequence_length1024►

◄cn_auto_scaletrue►

◄cn_target_strength1.0►

◄controlnet_conditioning_scale1.0►

◄control_guidance_start0.00►

◄control_guidance_end1.00►

◄s2_cn_scale1.0►

◄s2_cn_start0.00►

◄s2_cn_end1.00►

◄s1_mp0.5►

◄s1_steps15►

◄s1_cfg10.0►

◄upscale_to_stage24.0►

◄s2_steps26►

◄s2_cfg4.0►

◄s2_denoise0.85►

◄s2_sigma_schedulelinear►

◄upscale_to_stage32.0►

◄s3_steps18►

◄s3_cfg2.0►

◄s3_denoise0.45►

◄s3_sigma_schedulekarras►

◄upscale_vae_modeboth►

◄pad_edge_blur0.40►

CategoryEric Qwen-Image

Inputs (34)

Name	Type	Default	Description
pipeline	QWEN_IMAGE_PIPELINE		From the Qwen-Image loader or component loader
controlnet	QWEN_IMAGE_CONTROLNET		From the Qwen-Image ControlNet Loader
control_image	IMAGE		The control/condition image (canny edges, depth map, pose skeleton, or soft edges). Will be fitted to generation dimensions using cn_fit_mode.
cn_fit_mode	COMBO	match_control	How the control image is fitted to generation dimensions: • match_control — override aspect ratio to match control image • crop_center — scale to cover, center crop • crop_top_left/right — crop from corner • crop_bottom_left/right — crop from corner • pad_black_left/right/top/bottom — fit inside, pad with black • pad_edge_left/right/top/bottom — fit inside, extend edges with Gaussian feathering (ideal for depth maps) • stretch — distort to fill (legacy)
prompt	STRING		Describe the image you want to generate. For best results, use detailed descriptions (~200 words). Connect a Prompt Rewriter node to auto-enhance short prompts.
negative_promptopt	STRING	低分辨率，低画质，肢体畸形，手指畸形，画面过饱和，蜡像感，人脸无细节，过度光滑，画面具有AI感。构图混乱。文字模糊，扭曲。	What to avoid. Default is the official Qwen-Image-2512 negative prompt (Chinese).
aspect_ratioopt	COMBO	1:1 Square	Aspect ratio applied at every stage
seedopt	INT	00–18446744073709550000	Random seed (0 = random)
seed_modeopt	COMBO	offset_per_stage	How seeds are chosen for each stage: • same_all_stages — one generator for all stages • offset_per_stage — S2 uses seed+1, S3 uses seed+2 • random_per_stage — independent random seed per stage
max_sequence_lengthopt	INT	1024128–1024	Maximum prompt token length for the text encoder.
cn_auto_scaleopt	BOOLEAN	true	Auto-calibrate ControlNet strength to match the transformer's internal activation scale. Compensates for custom/finetuned transformers that have different hidden-state magnitudes than the base model the ControlNet was trained on. When enabled, cn_target_strength controls the final CN influence and conditioning_scale is ignored.
cn_target_strengthopt	FLOAT	1.00.1–6	ControlNet influence strength (auto-scale mode). 1.0 = standard (recommended starting point). 0.5 = subtle structural hints. 1.5–2.0 = strong structural guidance. 3.0+ = very strong (may over-constrain). Internally maps to hidden-state ratio (1.0 = 5%).
controlnet_conditioning_scaleopt	FLOAT	1.00–50	Manual ControlNet influence strength on Stage 1. Only used when cn_auto_scale is OFF. With custom/finetuned transformers, values of 10–30 may be needed (base model uses 1.0). 0.0 = ControlNet effectively disabled.
control_guidance_startopt	FLOAT	0.000–1	When ControlNet guidance begins (fraction of S1 steps). 0.0 = from the start (default).
control_guidance_endopt	FLOAT	1.000–1	When ControlNet guidance ends (fraction of S1 steps). 1.0 = through the end (default). 0.5 = ControlNet guides composition in early steps, then frees up for creative detail in later steps.
s2_cn_scaleopt	FLOAT	1.00–50	ControlNet influence strength on Stage 2. Only used when cn_auto_scale is OFF. When auto_scale is ON, S2 uses the same auto-calibrated factor as S1 (scaled by this value relative to S1 — e.g. 0.5 = half S1 strength). 0.0 = ControlNet disabled for S2.
s2_cn_startopt	FLOAT	0.000–1	When ControlNet guidance begins in Stage 2 (fraction of S2 steps). 0.0 = from the start.
s2_cn_endopt	FLOAT	1.000–1	When ControlNet guidance ends in Stage 2 (fraction of S2 steps). 1.0 = through the end (default). 0.5 = guide structure in early S2 steps only.
s1_mpopt	FLOAT	0.50.3–2	Stage 1 resolution in megapixels.
s1_stepsopt	INT	151–200	Stage 1 inference steps (ControlNet-guided txt2img)
s1_cfgopt	FLOAT	10.01–20	Stage 1 true CFG scale.
upscale_to_stage2opt	FLOAT	4.00–10	Upscale factor (area) from Stage 1 to Stage 2. Set to 0 to skip Stage 2 & 3 (output Stage 1 only).
s2_stepsopt	INT	261–200	Stage 2 inference steps (refinement, optional ControlNet).
s2_cfgopt	FLOAT	4.01–20	Stage 2 true CFG scale.
s2_denoiseopt	FLOAT	0.850.1–1	Stage 2 denoise strength.
s2_sigma_scheduleopt	COMBO	linear	Sigma schedule curve for Stage 2 refinement.
upscale_to_stage3opt	FLOAT	2.00–8	Upscale factor (area) from Stage 2 to Stage 3. Default 0 = disabled (2-stage output).
s3_stepsopt	INT	181–200	Stage 3 inference steps
s3_cfgopt	FLOAT	2.01–20	Stage 3 true CFG scale
s3_denoiseopt	FLOAT	0.450.1–1	Stage 3 denoise strength.
s3_sigma_scheduleopt	COMBO	karras	Sigma schedule curve for Stage 3 final polish.
upscale_vaeopt	UPSCALE_VAE		Optional: Wan2.1 2× upscale VAE. Load with Eric Qwen Upscale VAE Loader.
upscale_vae_modeopt	COMBO	both	How the upscale VAE is used (requires upscale_vae). • disabled — upscale VAE ignored • inter_stage — decode S2→2×→re-encode for S3 • final_decode — 2× upscale on final output • both — inter-stage + final decode
pad_edge_bluropt	FLOAT	0.400–1	Blur strength for pad_edge_* fit modes. Controls how far the Gaussian feather extends into the padding zone. • 0.0 = pure edge replication (may show bands at seam) • 0.4 = default — gentle, natural depth taper • 1.0 = heavy blur, very soft fade Has no effect on pad_black_* or other modes.

Outputs (1)

Name	Type	Description
image	IMAGE	—