--- tags: - text-to-image - lora - diffusers - template:diffusion-lora base_model: black-forest-labs/FLUX.1-Kontext-dev instance_prompt: >- [photo content], extract only the specified clothing item [full outfit, top wear, bottom wear, t-shirt, jacket, dress, etc.] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. license: apache-2.0 pipeline_tag: image-to-image library_name: diffusers --- ![1](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/UiBUzSy7Y9vGd6vUuc9as.png) # **Outfit-Cut** Outfit-Cut is an adapter for black-forest-lab's FLUX.1-Kontext-dev, designed to extract outfits from images based on precisely specified subjects. The model was trained on 200 image pairs (100 start images and 100 end images). The adapter can be triggered with the following prompt: > [!note] [photo content], extract only the specified clothing item [full outfit, top wear, bottom wear, t-shirt, jacket, dress, etc.] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. ## Sample Inference > Prompt: [photo content], extract only the specified clothing item [t-shirt] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. | ![ee0a972e52b06f169778570a950118e6](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/rHjF9Uy0529fqGajjDwxI.jpeg) | ![1111111111111111111](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/McZET62QQXHDKVSO-Dcyo.webp) | |---|---| --- > Prompt: [photo content], extract only the specified clothing item [top wear] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. | ![79e7436e24d4e9b6156f87d9cb9f4bc3](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/XMX3qCoUP3Qfxd89oDZso.jpeg) | ![2222222222222222222222222](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/o9c-hGihXRO14wwvWmvbR.webp) | |---|---| --- > Prompt: [photo content], extract only the specified clothing item [t-shirt] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. | ![fafd6d019bdafeb9547f2f1540e23995](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/_I2dr8VO1_WHJBiWuLD3J.jpeg) | ![2222222222222222222](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/mBVY-NYP1RapP2USr93KQ.webp) | |---|---| --- > Prompt: [photo content], extract only the specified clothing item [t-shirt] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. | ![7384a0570678406a47c63d0e3e84f021](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/_AV_Wiv4jpKDMTwfJ6DvT.jpeg) | ![4444444444444444](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/nQoHt3be0BSTIuOdjM7QU.webp) | |---|---| --- > Prompt: [photo content], extract only the specified clothing item [t-shirt] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. | ![fc828e484d937733188d82252c08ae79](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/vbIu4c1uQSqMDmAUlzP-a.jpeg) | ![3333333](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/YPVunuWm_BbLHi6986Pal.webp) | |---|---| --- > Prompt: [photo content], extract only the specified clothing item [t-shirt] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. | ![57ed147059b2a34e578287ade0890210](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/quxI-kx_J6VDpF7ybQhyF.jpeg) | ![Untitled](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/NZCRnuh0UeNmckGKpY5HP.webp) | |---|---| --- > [!note] Note: This adapter works well for extracting top wear (t-shirts, shirts, jackets, hoodies). The model may perform sub-optimally in more challenging cases, such as full clothing extraction, poorly lit images, and other difficult scenarios. --- ## Parameter Settings | Setting | Value | | ------------------------ | ------------------------ | | Module Type | Adapter | | Base Model | FLUX.1 Kontext Dev - fp8 | | Trigger Words | [photo content], extract only the specified clothing item [top wear, bottom wear] from the image and place it over a clean, plain background. Present the result in a product photography style — well-lit, crisp, and professional — while preserving the garment’s original textures, colors, shapes, and fine details. | | Image Processing Repeats | 50 | | Epochs | 25 | | Save Every N Epochs | 1 | Labeling: DeepCaption-VLA-7B(natural language & English) Total Images Used for Training : 200 Image Pairs (100 Start, 100 End) ## Training Parameters | Setting | Value | | --------------------------- | --------- | | Seed | - | | Clip Skip | - | | Text Encoder LR | 0.00001 | | UNet LR | 0.00005 | | LR Scheduler | constant | | Optimizer | AdamW8bit | | Network Dimension | 64 | | Network Alpha | 32 | | Gradient Accumulation Steps | - | ## Label Parameters | Setting | Value | | --------------- | ----- | | Shuffle Caption | - | | Keep N Tokens | - | ## Advanced Parameters | Setting | Value | | ------------------------- | ----- | | Noise Offset | 0.03 | | Multires Noise Discount | 0.1 | | Multires Noise Iterations | 10 | | Conv Dimension | - | | Conv Alpha | - | | Batch Size | - | | Steps | 2700 | | Sampler | euler | --- ## Trigger words You should use `[photo content]` to trigger the image generation. You should use `extract only the specified clothing item [full outfit` to trigger the image generation. You should use `top wear` to trigger the image generation. You should use `bottom wear` to trigger the image generation. You should use `t-shirt` to trigger the image generation. You should use `jacket` to trigger the image generation. You should use `dress` to trigger the image generation. You should use `etc.] from the image and place it over a clean` to trigger the image generation. You should use `plain background. Present the result in a product photography style — well-lit` to trigger the image generation. You should use `crisp` to trigger the image generation. You should use `and professional — while preserving the garment’s original textures` to trigger the image generation. You should use `colors` to trigger the image generation. You should use `shapes` to trigger the image generation. You should use `and fine details.` to trigger the image generation. ## Download model [Download](/prithivMLmods/Outfit-Cut/tree/main) them in the Files & versions tab.