Qwen Edit 2509 MultipleAngles | Multi-View Image Creator

Qwen Edit 2509 MultipleAngles: multi‑view image edits from a single reference

Qwen Edit 2509 MultipleAngles is a ComfyUI workflow that generates consistent multi‑angle views from one input image. Give it a character, product, prop, or scene and it reframes the subject into front, side, three‑quarter, close‑up, or top‑down perspectives while preserving identity and style. Powered by Qwen‑Image editing and a compact instruction setup, this workflow is ideal for character design, product visualization, look‑dev, and animation prep.

The workflow combines Qwen Edit 2509 MultipleAngles conditioning with a camera‑aware LoRA stack and a fast sampler, so you can iterate quickly across different viewpoints. You control angles through short, natural instructions; the graph handles reference analysis, latent preparation, guidance, and decoding to produce ready‑to‑use images.

Key models in Comfyui Qwen Edit 2509 MultipleAngles workflow

• Qwen/Qwen-Image. Foundation diffusion model used here for image editing and view synthesis; provides strong identity preservation and text‑guided edits. Hugging Face Technical report
• Qwen/Qwen2.5‑VL‑7B (text‑vision encoder). Supplies multilingual prompt understanding and visual‑language features that condition the image edits. A common distribution for local use is the instruction‑tuned 7B variant. Hugging Face
• Qwen‑Image VAE. Paired variational autoencoder used to decode latents back to images in ComfyUI builds of Qwen‑Image. Hugging Face
• Qwen‑Image‑Lightning LoRA (8‑step preset). Optional acceleration and quality tuning for fast edits in this workflow. Hugging Face

How to use Comfyui Qwen Edit 2509 MultipleAngles workflow

This graph follows a clean path from reference image and instruction to two decode branches. You will upload one image, choose or edit an angle instruction, and queue. Internally the workflow prepares conditioning with Qwen Edit 2509 MultipleAngles, applies a camera‑aware LoRA stack, samples twice, and saves both results.

Stage 1 — Reference and base loaders

• LoadImage (#13) is where you drop your single reference. Use a clear, centered subject for best multi‑view consistency. The workflow also loads the Qwen text‑vision encoder via CLIPLoader (#1), the Qwen‑Image UNet through UNETLoader (#17), and the paired decoder with VAELoader (#4). Together these nodes establish the model trio required for Qwen‑Image editing and decoding.

Stage 2 — Behavior LoRAs and model patching

• The stack of LoraLoaderModelOnly nodes injects behavior critical to Qwen Edit 2509 MultipleAngles. One LoRA provides multi‑angle editing priors (#16), another enables camera step transitions (#19), and an optional Lightning speed preset (#18) shortens sampling while preserving structure. The outputs feed ModelSamplingAuraFlow (#25, #27), after which CFGNorm (#24, #26) stabilizes guidance so edits remain faithful to the reference. You do not need to tweak anything here to get started; the defaults are balanced for reliable angle changes.

Stage 3 — Angle instructions and prompt routing

• The angle you want is set with the bilingual list in Text Multiline (#20). easy promptLine (#3) selects one line and forwards it, such as “Next Scene: Rotate the camera 45 degrees to the left” or “Turn the camera to a top‑down view.” You can replace or add lines with your own phrasing (for example, “front view,” “right three‑quarter,” “close‑up on face with shallow depth of field”). Keep instructions short and camera‑focused for predictable multi‑angle outputs from Qwen Edit 2509 MultipleAngles.

Stage 4 — Conditioning and latent setup

• TextEncodeQwenImageEditPlusAdvance_lrzjason (#14) analyzes the reference image and merges it with your instruction to produce both conditioning and a prepared latent. It handles resizing and crop strategy internally so the subject remains centered and consistent across angles. An optional instruction field inside this node can be used for extra guidance like identity notes, material cues, or style boundaries. The negative path is intentionally neutralized by ConditioningZeroOut (#10) so the edit focuses on view change rather than suppression.

Stage 5 — Sampling, decoding, and outputs

• Two KSampler nodes (#12 and #21) generate latents using the conditioned model and the patched variant; this often yields a paired set that differs slightly in composition or micro‑detail. The results are decoded by VAEDecode (#7, #22) and written out by SaveImage (#11, #23). Use the same seed to compare angles consistently, or change the seed to explore alternates while keeping viewpoint intent. You now have multiple angles produced by the Qwen Edit 2509 MultipleAngles pipeline, ready for boards, turnarounds, or downstream paint‑overs.

Key nodes in Comfyui Qwen Edit 2509 MultipleAngles workflow

TextEncodeQwenImageEditPlusAdvance_lrzjason (#14)

• This is the heart of Qwen Edit 2509 MultipleAngles. It fuses your reference with the angle instruction to produce conditioning and a starting latent. Adjust instruction when you need stricter identity or style constraints, and refine framing with target_size and crop_method if parts of the subject are cropped. Use concise directives like “front view,” “left three‑quarter,” or “top‑down close‑up.”

LoraLoaderModelOnly (#16) — Multiple‑angles LoRA

• Governs viewpoint reinterpretation while maintaining identity. Increase strength_model for stronger angle enforcement; reduce it if facial features or logos drift. Use small changes and re‑queue to find the balance between pose change and fidelity.

LoraLoaderModelOnly (#18) — Qwen‑Image‑Lightning

• Provides faster convergence for edits with very few steps. If textures look oversmoothed, lower strength_model slightly or pair with a few more sampler steps. Keep it enabled when you need quick multi‑angle previews from Qwen Edit 2509 MultipleAngles.

ModelSamplingAuraFlow (#25, #27)

• Adapts the edited model to a flow‑style sampler schedule for stable, fast updates. The shift control subtly trades crispness for smoothness; leave near default for most subjects. Use this in tandem with CFGNorm to keep guidance predictable as you vary instructions.

CFGNorm (#24, #26)

• Normalizes classifier‑free guidance to reduce over‑ or under‑steering. A modest strength keeps angles consistent without washing out subject identity. If you see exaggerated artifacts when pushing camera extremes, nudge this slightly upward.

KSampler (#21)

• Main quality lever for sampling. steps increases detail, cfg strengthens prompt adherence, denoise sets how far the view can diverge from the reference, and seed controls repeatability. For turnarounds, fix the seed and vary the instruction; for exploration, vary both.

Optional extras

• Write angle instructions in plain language: “front view,” “profile left,” “low‑angle close‑up,” “bird’s‑eye product shot,” “three‑quarter hero shot.”
• For identity‑critical subjects, add a short identity reminder in the node instruction field (#14), such as “keep hairstyle and eye color identical; preserve logo text.”
• If the subject crops too tightly, try a wider instruction (wide angle, step back, top‑down) or adjust crop_method in (#14).
• Keep LoRA strengths conservative when mixing multiple behaviors; small changes can have outsized effects on angle and pose in Qwen Edit 2509 MultipleAngles.

Acknowledgements

This workflow implements and builds upon the following works and resources. We gratefully acknowledge the CivitAI community for the Qwen-Edit2509 Multi-Angle Storyboard Direct Output workflow for their contributions and maintenance. For authoritative details, please refer to the original documentation and repositories linked below.

Resources

• CivitAI/Qwen-Edit2509 Multi-Angle Storyboard Direct Output
  • Docs / Release Notes: CivitAI Workflow Source

Note: Use of the referenced models, datasets, and code is subject to the respective licenses and terms provided by their authors and maintainers.