Image Segmentation
Diffusers
Safetensors
remote-sensing
change-detection
semantic-segmentation
diffusion
earth-observation
Instructions to use ali97/noise2map with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ali97/noise2map with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ali97/noise2map", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -34,9 +34,9 @@ Pretrained denoising UNet backbones for **Noise2Map: End-to-End Diffusion Model
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## Usage
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```python
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from noise2map import
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model =
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in_channels=6, # 3 for semantic segmentation
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out_channels=2,
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img_scale=256,
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## Usage
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```python
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from noise2map import Noise2Map
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model = Noise2Map(
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in_channels=6, # 3 for semantic segmentation
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out_channels=2,
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img_scale=256,
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