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  "path": "/t/help-looking-for-smart-object-swap-model-with-reference/175385#post_2",
  "publishedAt": "2026-04-20T00:02:34.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "image-to-image models",
    "openaccess.thecvf.com",
    "huggingface.co",
    "xavierchen34.github.io"
  ],
  "textContent": "What about image-to-image models?\n\n* * *\n\nYou are looking for a model that can do **reference-driven object replacement** , not just ordinary prompt-based editing.\n\nThat distinction is the whole story.\n\nMost image editors are good at:\n\n  * “make this object look nicer,”\n  * “change the style,”\n  * “replace the object with a plausible new object.”\n\n\n\nBut you want something stronger:\n\n> **Take object B from a reference image, and install it into image A, ideally in a chosen region, while preserving the rest of image A.**\n\nThat is a much narrower and harder task. It sits between **inpainting** , **image editing** , **reference-guided generation** , and **object-level compositing**. That is why so many otherwise impressive models have not worked for you. (openaccess.thecvf.com)\n\n## The big picture\n\nFor your use case, the useful models fall into **two families** :\n\n### Family A — direct-fit models\n\nThese are the ones that are conceptually closest to your task:\n\n  * **AnyDoor**\n  * **MimicBrush**\n  * **FLUX.1 Kontext Inpaint**\n(huggingface.co)\n\n\n\nThese are the best when you can provide:\n\n  * a base image,\n  * a reference object image,\n  * and ideally a mask or target region.\n\n\n\n### Family B — latest general HF editors that are now strong enough to try\n\nThese are newer, broader, more modern image editors that can often do the job if you set them up well:\n\n  * **`black-forest-labs/FLUX.2-klein-4B`**\n  * **`Qwen/Qwen-Image-Edit-2511`**\n  * **`FireRedTeam/FireRed-Image-Edit-1.1`**\n  * **`meituan-longcat/LongCat-Image-Edit`**\n  * **`black-forest-labs/FLUX.2-dev`** if you can handle a large model\n(huggingface.co)\n\n\n\nMy real opinion is:\n\n  * **If you care about task fit, think like Family A.**\n  * **If you care about Hugging Face practicality in 2026, start testing Family B.**\n\n\n\nThat is the cleanest summary I can give.\n\n* * *\n\n## My honest recommendation, in plain language\n\nIf I were doing this myself, I would not hunt for a single “perfect” model first.\n\nI would use this strategy:\n\n### Best practical first test\n\n**`black-forest-labs/FLUX.2-klein-4B`**\nbecause it is:\n\n  * current,\n  * supports **multi-reference editing** ,\n  * small enough to be practical,\n  * and **Apache-2.0**. (huggingface.co)\n\n\n\n### Best mature open baseline\n\n**`Qwen/Qwen-Image-Edit-2511`**\nbecause the Diffusers docs explicitly support **multi-image reference** workflows, and Qwen has become one of the safest open editing baselines on Hugging Face. (huggingface.co)\n\n### Best for identity consistency\n\n**`FireRedTeam/FireRed-Image-Edit-1.1`**\nbecause its model card explicitly emphasizes **identity consistency** and **multi-image conditioning** , which are exactly the two things that usually break in reference-based object replacement. (huggingface.co)\n\n### Best for localized reference-guided editing\n\n**`meituan-longcat/LongCat-Image-Edit`**\nbecause the card explicitly says it supports **local editing** and **reference-guided editing**. That makes it unusually relevant to what you are trying to do. (huggingface.co)\n\n### Best conceptual research fit\n\n**AnyDoor**\nbecause the paper is still one of the closest direct matches to “swap object in scene using object reference.” (openaccess.thecvf.com)\n\n### Best shape-preserving reference imitation\n\n**MimicBrush**\nbecause it is built around source image + selected region + reference image, and is especially good when the edit is more like **“make this region become like the reference”** than **“fully reconstruct a new rigid object from scratch.”** (xavierchen34.github.io)\n\n* * *\n\n## The single most important thing: use a mask if you can\n\nYou said a third image with the masked area is an option.\n\nThat is not a fallback. That is a major advantage.\n\nIn practice, the masked version of your problem is much easier than the unmasked version, because the model no longer has to guess:\n\n  * what to replace,\n  * where to replace it,\n  * and how much of the scene should stay untouched. (huggingface.co)\n\n\n\nSo I would strongly reframe the situation like this:\n\n  * **Two images only** = hard mode\n  * **Base image + reference object + target mask** = realistic mode\n\n\n\nThat is one of the biggest reasons people fail with this class of task. They are asking the model to solve localization, object transfer, and blending all at once. (openaccess.thecvf.com)\n\n* * *\n\n## Why general editors often fail here\n\nThere are four common failure modes.\n\n## 1) The model preserves the category, not the instance\n\nIt gives you “a similar object,” not **the actual reference object**.\nThis is the classic identity-drift problem. It is exactly why I think FireRed is worth testing early, and why AnyDoor still matters conceptually. (huggingface.co)\n\n## 2) The model edits too much\n\nIt changes the surrounding image when you only wanted one region edited.\nThat is why masked editing and locality-aware models matter so much. (huggingface.co)\n\n## 3) The model gets the geometry wrong\n\nThe object looks plausible by itself, but does not fit the target scene:\n\n  * wrong perspective,\n  * wrong scale,\n  * wrong orientation,\n  * wrong relation to nearby objects.\nThat is where more spatially aware editors, or models that accept a mask/target region, help a lot. (huggingface.co)\n\n\n\n## 4) The reference image carries too much clutter\n\nIf the reference contains extra background, lighting, or surrounding objects, the model may import the wrong things.\nThe AnyDoor paper explicitly reports that filtering background information from the reference object helps. (openaccess.thecvf.com)\n\n* * *\n\n## Detailed model-by-model thoughts\n\n## 1) AnyDoor\n\n### What it is\n\nA research-oriented object-level image customization method designed for tasks like object insertion and object swapping. (openaccess.thecvf.com)\n\n### Why it matches your request so well\n\nBecause its whole framing is basically:\n\n  * take a base image,\n  * take a reference object,\n  * place/swap that object into the base image. (openaccess.thecvf.com)\n\n\n\n### Why I do not recommend it as the easiest first option\n\nBecause the current Hugging Face Space shows a **runtime error** , so the practical HF experience is not as clean as with the newer families. (huggingface.co)\n\n### My real conclusion\n\n**Excellent conceptual fit.**\n**Not the cleanest beginner-first Hugging Face experience today.**\n\n* * *\n\n## 2) FLUX.1 Kontext Inpaint\n\n### What it is\n\nA Diffusers pipeline that explicitly supports:\n\n  * editing within a **fixed mask region**\n  * with **image-reference conditioning**. (huggingface.co)\n\n\n\n### Why it matters so much\n\nBecause many models say “editing,” but the docs do not clearly spell out the exact local workflow. Kontext does. That makes it one of the most concrete “yes, this really matches your problem” options in the HF ecosystem. (huggingface.co)\n\n### My real conclusion\n\nIf you can provide a mask, this is one of the strongest **practical** paths, even though newer general models now exist.\n\n* * *\n\n## 3) FLUX.2-klein-4B\n\n### What it is\n\nA newer FLUX.2 model with:\n\n  * **multi-reference editing**\n  * consumer-GPU friendliness\n  * **Apache-2.0** licensing\n  * release date **April 6, 2026**. (huggingface.co)\n\n\n\n### Why I like it for your case\n\nIt hits a rare sweet spot:\n\n  * current,\n  * practical,\n  * open enough,\n  * and explicitly reference-aware. (huggingface.co)\n\n\n\n### Weak point\n\nIt is still a broader general editor family, not a pure object-swap paper architecture. So it may still need strong masking and good setup to shine.\n\n### My real conclusion\n\nIf you ask me for **one Hugging Face model to try first today** , this is near the top of the list.\n\n* * *\n\n## 4) Qwen-Image-Edit-2511\n\n### What it is\n\nA strong open editing model with documented support for **multi-image reference workflows** in Diffusers. (huggingface.co)\n\n### Why I like it\n\nBecause it is one of the cleanest current “modern open image editor” stacks:\n\n  * active,\n  * documented,\n  * relatively standard to use,\n  * and not locked into obscure tooling. (huggingface.co)\n\n\n\n### Weak point\n\nIt is broader than your exact task. It is not a pure object-swap specialist the way AnyDoor is.\n\n### My real conclusion\n\nThis is the model I would use as a **strong open baseline**. If even this struggles with your case, that is useful information.\n\n* * *\n\n## 5) FireRed-Image-Edit-1.1\n\n### What it is\n\nA general-purpose image editing model whose card explicitly highlights:\n\n  * **identity consistency**\n  * **multi-image conditioning**\n  * real-world editing performance. (huggingface.co)\n\n\n\n### Why I like it for your problem\n\nBecause the biggest pain in reference-object swap is often:\n\n> “The edit happened, but the model did not really preserve the referenced object.”\n\nThat is the exact axis where FireRed is trying to improve. (huggingface.co)\n\n### My real conclusion\n\nIf your current attempts produce generic-looking replacements, test FireRed early.\n\n* * *\n\n## 6) LongCat-Image-Edit\n\n### What it is\n\nA model card that explicitly says:\n\n  * global editing,\n  * local editing,\n  * text modification,\n  * **reference-guided editing**. (huggingface.co)\n\n\n\n### Why that matters\n\nThat wording is unusually aligned with your problem. It suggests a model that was designed with more structured edit control in mind, not just flashy broad edits.\n\n### My real conclusion\n\nThis is a strong candidate if your problem is mostly:\n\n  * “edit only this region”\n  * “follow the reference carefully”\n  * “do not wreck the rest of the image”\n\n\n\n* * *\n\n## 7) MimicBrush\n\n### What it is\n\nA project focused on local reference imitation:\n\n  * source image,\n  * selected edit region,\n  * reference image. (xavierchen34.github.io)\n\n\n\n### Why it matters\n\nBecause it directly respects the way you think about the task: not “prompt first,” but “image first.”\nIt is especially appealing when the edit is about making the target region **look like** the reference, while preserving more of the original shape. (xavierchen34.github.io)\n\n### Weak point\n\nThe current HF Space shows a **configuration error**. (huggingface.co)\n\n### My real conclusion\n\nUseful, relevant, but more research/project-flavored than modern HF-native turnkey.\n\n* * *\n\n## My recommended testing order\n\nHere is the order I would actually use.\n\n## First wave\n\nThese give the best balance of practicality and relevance:\n\n  1. **FLUX.2-klein-4B**\n  2. **Qwen-Image-Edit-2511**\n  3. **FireRed-Image-Edit-1.1**\n  4. **LongCat-Image-Edit**\n(huggingface.co)\n\n\n\nThis wave tells you whether the problem is already solvable with current modern HF-native editors.\n\n## Second wave\n\nIf the first wave is close but not quite right:\n\n  1. **FLUX Kontext masked reference path**\n  2. **AnyDoor**\n  3. **MimicBrush**\n(huggingface.co)\n\n\n\nThis wave tells you whether the missing ingredient is **more explicit locality/object-level structure** , not more raw model power.\n\n## Third wave\n\nOnly if you have heavy compute and want to test the ceiling:\n\n  1. **FLUX.2-dev**\n(huggingface.co)\n\n\n\n* * *\n\n## Practical setup advice\n\nThese details matter a lot.\n\n## 1) Prepare the reference object well\n\nUse a **tight crop** or segmented object if possible.\nDo not feed a messy reference image if you can avoid it. (openaccess.thecvf.com)\n\n## 2) Prepare a real mask\n\nIf possible, the mask should cover the exact region you want replaced, not a huge loose box.\nPrecise locality is a big part of success. (huggingface.co)\n\n## 3) Crop around the edit region\n\nIf the region is small relative to the full image, cropping around it helps the model focus. The Diffusers docs explicitly mention this for local inpainting-style workflows. (huggingface.co)\n\n## 4) Keep the instruction short and concrete\n\nEven in image-led editing, a small prompt helps:\n\n  * “replace the masked object with the reference object”\n  * “keep the rest of the image unchanged”\n  * “preserve lighting, scale, and perspective”\n\n\n\nShort, concrete, and visual is usually better than long creative prose.\nThe FLUX.2 editing app prompt rules are actually quite aligned with that style. (huggingface.co)\n\n* * *\n\n## Final verdict\n\nIf you want the answer reduced to one clear recommendation:\n\n### Best overall practical strategy\n\n**Use a mask and test modern HF-native editors first.**\n\n### Best first HF model to try\n\n**`black-forest-labs/FLUX.2-klein-4B`**\nbecause it is recent, open enough, multi-reference capable, and practical. (huggingface.co)\n\n### Best open baseline\n\n**`Qwen/Qwen-Image-Edit-2511`**. (huggingface.co)\n\n### Best identity-focused alternative\n\n**`FireRedTeam/FireRed-Image-Edit-1.1`**. (huggingface.co)\n\n### Best locality-focused alternative\n\n**`meituan-longcat/LongCat-Image-Edit`**. (huggingface.co)\n\n### Best conceptual specialist\n\n**AnyDoor**. (openaccess.thecvf.com)\n\n* * *\n\nHere is the **compact, concrete start-here recipe** I would use for your task.\n\n## 1) Prepare exactly these 3 inputs\n\n**Input A — base image**\nThe image you want to edit.\n\n**Input B — reference object image**\nA **tight crop** of the object you want to insert/transfer. Remove as much background as possible. The AnyDoor paper reports better results when background information around the reference object is filtered out. (openaccess.thecvf.com)\n\n**Input C — mask image**\nA mask of the region to replace. If you can provide this, do it. It makes the task much easier and much more controllable. Diffusers’ FLUX Kontext docs explicitly support **image-reference conditioning inside a fixed mask region**. (huggingface.co)\n\n## 2) Crop the work area before editing\n\nDo **not** always feed the entire full-resolution image first.\n\nIf the target region is small, crop around that region plus a little context. The Diffusers docs explicitly note that when the masked region is small compared with the whole image, cropping around it can improve results. (huggingface.co)\n\n## 3) Try these models in this exact order\n\n### First try\n\n**FLUX Kontext masked reference workflow**\nReason: this is the clearest officially documented Hugging Face path for **masked local editing + image-reference conditioning**. (huggingface.co)\n\n### Second try\n\n**`black-forest-labs/FLUX.2-klein-4B`**\nReason: it is current, practical, **Apache-2.0** , and its card explicitly says it supports **image-to-image multi-reference editing**. (huggingface.co)\n\n### Third try\n\n**`Qwen/Qwen-Image-Edit-2511`**\nReason: it is a strong open baseline, and Diffusers explicitly documents **multi-image reference** workflows for the Qwen image editing family. (huggingface.co)\n\n### Backup if those are close but not good enough\n\n**`meituan-longcat/LongCat-Image-Edit`**\nReason: the card explicitly says it supports **local editing** and **reference-guided editing**. (huggingface.co)\n\n## 4) Use a short prompt, not a long one\n\nUse something like this:\n\n> **Replace the masked object with the reference object. Keep the rest of the image unchanged. Match scale, lighting, and perspective.**\n\nDo not write a long creative paragraph. Keep it direct and visual.\n\n## 5) Run the same 3 tests for every model\n\nFor each model, do these 3 runs:\n\n### Run A — clean reference + clean mask\n\nThis is your baseline.\n\n### Run B — same inputs, slightly larger mask\n\nThis checks whether the model needed a bit more freedom around edges.\n\n### Run C — same inputs, tighter crop around the target region\n\nThis checks whether the full image was distracting the model.\n\n## 6) Diagnose failure like this\n\n### If the model changes too much of the image\n\nProblem: weak locality.\nAction: use a **better mask** , **tighter crop** , or switch toward **Kontext / LongCat**. (huggingface.co)\n\n### If the model inserts the wrong-looking object\n\nProblem: reference identity drift.\nAction: clean the reference crop more aggressively; then try **Qwen** or **FLUX.2-klein-4B** again. The AnyDoor paper and newer model cards both point to reference handling as a key issue. (openaccess.thecvf.com)\n\n### If the object looks right but fits badly in the scene\n\nProblem: geometry / perspective / scene integration.\nAction: enlarge the crop around the target area a bit and make the prompt explicitly say **match scale, lighting, and perspective**.\n\n### If everything is almost right except the edges\n\nProblem: blending.\nAction: rerun with a slightly larger mask, then do a second cleanup pass.\n\n## 7) The shortest realistic recommendation\n\nIf you want the fastest sensible path:\n\n  1. **Prepare:** base image + tight reference crop + mask.\n  2. **Test first:** **FLUX Kontext masked reference path**.\n  3. **Test second:** **FLUX.2-klein-4B**.\n  4. **Test third:** **Qwen-Image-Edit-2511**.\n  5. **If locality is still weak:** try **LongCat-Image-Edit**.\n\n",
  "title": "Help... looking for Smart Object Swap model with reference"
}