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