DDPM Uwall Morefields

--- license: mit tags: - pytorch - diffusers - unconditional-image-generation - diffusion-models-class library_name: diffusers --- This model is a diffusion model for unconditional image generation of uwall velocity field in a turbulent channel flow with Retau = 1000. This model is trained using just almost 1000 fields which are very few since in the most of case DDPM are trained with thousands of images. ## Usage ```python from diffusers import DDPMPipeline import torch import torchvision from torchvision import transforms import numpy as np from matplotlib import pyplot as plt from huggingface_hub import hf_hub_download import joblib pipeline = DDPMPipeline.from_pretrained('RobbyDalmonts/DDPM_uwall_morefields') image = pipeline().images[0] to_tensor = transforms.ToTensor() tensor_output_normalized = to_tensor(image) tensor_output_normalized = tensor_output_normalized *2 -1 fig,ax = plt.subplots() ax.imshow(tensor_output_normalized[0], cmap ='coolwarm') ax.set_title('normalized sample') plt.show() plt.close() scaler_path = hf_hub_download(repo_id='RobbyDalmonts/DDPM_uwall_morefields', filename="scaler.pkl", repo_type='model') scaler = joblib.load(scaler_path) tensor_output = scaler.inverse_transform(tensor_output_normalized.squeeze(0).numpy().reshape(-1,1)).reshape(128,64) fig,ax = plt.subplots() ax.imshow(tensor_output, cmap='coolwarm') ax.set_title('sample') plt.show() plt.close() ```

Source context: 10 downloads · 0 likes · Pipeline unconditional-image-generation · Library diffusers · Repo RobbyDalmonts/DDPM_uwall_morefields