InScene: Flux.1-Kontext.dev LoRA

InScene is a LoRA trained by Peter O’Malley 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