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--- |
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license: apache-2.0 |
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datasets: |
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- peteromallet/InScene-Dataset |
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base_model: |
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- black-forest-labs/FLUX.1-Kontext-dev |
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tags: |
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- image |
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- editing |
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- lora |
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- diffusers |
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pipeline_tag: image-to-image |
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--- |
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# InScene: Flux.1-Kontext.dev LoRA |
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## Model Description |
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**InScene** is a LoRA for Flux.Kontext.dev that's designed to generate images that maintain scene consistency with a source image. It is trained on top of Flux.1-Kontext.dev. |
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The primary use case is to generate variations of a shot while keeping the background and overall environment, characters, and styles the same: |
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## How to Use |
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To get the best results, start your prompt with the phrase: |
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`Make a shot in the same scene of ` |
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And describe your new image. |
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For example: |
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`Make a shot in the same scene of the car up very close to the camera with the driver smiling manically.` |
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### Strengths & Weaknesses |
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The model excels at: |
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- Generating realistic shots that are consistent with the original scene. |
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- Handling most common photographic and artistic styles. |
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The model may struggle with: |
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- Action-oriented prompts (e.g., "punching", "running"). |
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- Uncommon or highly abstract styles. |
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## Training Data |
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The `InScene` LoRA was trained on 394 image pairs. This dataset was created by extracting and enriching frames from the WebVid dataset. |
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You can find the public dataset used for training here: |
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[https://huggingface.co/datasets/peteromallet/InScene-Dataset](https://huggingface.co/datasets/peteromallet/InScene-Dataset) |
