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prithivMLmods/Kontext-Bottom-Up-View
Kontext-Bottom-Up-View is a image-to-image model from prithivMLmods. Use it when you need one image transformed into another. It is set up for transformers. The card lists the license as other.
Downloads · 30 days
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Updated Nov 8, 2025
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From the Hugging Face model README

The Kontext-Bottom-Up-View is an experimental adapter for black-forest-lab's FLUX.1-Kontext-dev, designed to transform scenes into a bottom-up perspective, preserving accurate depth, scale, and lighting direction to enhance overall realism. The model ensures that background elements such as sky or ground surfaces adjust naturally to the new viewing angle, maintaining coherent geometry, texture consistency, and visual balance. It was trained on 800 image pairs (400 start images and 400 end images) to achieve precise, geometry-consistent bottom-up scene generation.
[!note] [photo content], recreate the scene from a bottom-up perspective. Preserve accurate depth, scale, and lighting direction to enhance realism. Ensure the background sky or floor elements adjust naturally to the new angle, maintaining authentic shadowing and perspective.
You modified the prompt, altering its properties and subjective elements. Note: this is an experimental adapter and may contain artifacts.
| Setting | Value |
|---|---|
| Module Type | Adapter |
| Base Model | FLUX.1 Kontext Dev - fp8 |
| Trigger Words | [photo content], recreate the scene from a bottom-up perspective. Preserve accurate depth, scale, and lighting direction to enhance realism. Ensure the background sky or floor elements adjust naturally to the new angle, maintaining authentic shadowing and perspective. |
| Image Processing Repeats | 45 |
| Epochs | 24 |
| Save Every N Epochs | 1 |
Labeling: DeepCaption-VLA-7B(natural language & English)
Total Images Used for Training : 800 Image Pairs (400 Start, 400 End)
| 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 | - |
| Setting | Value |
|---|---|
| Shuffle Caption | - |
| Keep N Tokens | - |
| Setting | Value |
|---|---|
| Noise Offset | 0.03 |
| Multires Noise Discount | 0.1 |
| Multires Noise Iterations | 10 |
| Conv Dimension | - |
| Conv Alpha | - |
| Batch Size | - |
| Steps | 3500 & 400(warm up) |
| Sampler | euler |
You should use [photo content] to trigger the image generation.
You should use recreate the scene from a bottom-up perspective. Preserve accurate depth to trigger the image generation.
You should use scale to trigger the image generation.
You should use and lighting direction to enhance realism. Ensure the background sky or floor elements adjust naturally to the new angle to trigger the image generation.
You should use maintaining authentic shadowing and perspective. to trigger the image generation.
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