osanseviero multimodalart HF staff commited on
Commit
3c7cefd
1 Parent(s): 8ad58ba

Update in line with the other spaces (#1)

Browse files

- Update in line with the other spaces (4b1061b78912458a65f7a36808d3148bd1b01d79)


Co-authored-by: Multimodal AI art <multimodalart@users.noreply.huggingface.co>

Files changed (1) hide show
  1. app.py +10 -6
app.py CHANGED
@@ -2,10 +2,10 @@ from diffusers import LatentDiffusionUncondPipeline
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  import torch
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  import PIL.Image
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  import gradio as gr
 
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  import numpy as np
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- pipeline = LatentDiffusionUncondPipeline.from_pretrained("CompVis/latent-diffusion-celeba-256")
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-
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  def predict(steps=1, seed=42):
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  generator = torch.manual_seed(seed)
@@ -14,12 +14,16 @@ def predict(steps=1, seed=42):
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  image_processed = (image_processed + 1.0) * 127.5
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  image_processed = image_processed.clamp(0, 255).numpy().astype(np.uint8)
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  return PIL.Image.fromarray(image_processed[0])
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-
 
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  gr.Interface(
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  predict,
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  inputs=[
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- gr.inputs.Slider(1, 10, label='Inference Steps', default=1, step=1),
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- gr.inputs.Slider(0, 1000, label='Seed', default=42),
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  ],
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- outputs="image",
 
 
 
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  ).launch()
 
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  import torch
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  import PIL.Image
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  import gradio as gr
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+ import random
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  import numpy as np
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+ pipeline = LatentDiffusionUncondPipeline.from_pretrained("CompVis/ldm-celebahq-256")
 
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  def predict(steps=1, seed=42):
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  generator = torch.manual_seed(seed)
 
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  image_processed = (image_processed + 1.0) * 127.5
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  image_processed = image_processed.clamp(0, 255).numpy().astype(np.uint8)
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  return PIL.Image.fromarray(image_processed[0])
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+
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+ random_seed = random.randint(0, 2147483647)
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  gr.Interface(
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  predict,
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  inputs=[
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+ gr.inputs.Slider(1, 100, label='Inference Steps', default=5, step=1),
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+ gr.inputs.Slider(0, 2147483647, label='Seed', default=random_seed, step=1),
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  ],
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+ outputs=gr.Image(shape=[256,256], type="pil", elem_id="output_image"),
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+ css="#output_image{width: 256px}",
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+ title="ldm-celebahq-256 - 🧨 diffusers library",
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+ description="This Spaces contains an unconditional Latent Diffusion process for the <a href=\"https://huggingface.co/CompVis/ldm-celebahq-256\">ldm-celebahq-256</a> face generator model by <a href=\"https://huggingface.co/CompVis\">CompVis</a> using the <a href=\"https://github.com/huggingface/diffusers\">diffusers library</a>. The goal of this demo is to showcase the diffusers library capabilities. If you want the state-of-the-art experience with Latent Diffusion text-to-image check out the <a href=\"https://huggingface.co/spaces/multimodalart/latentdiffusion\">main Spaces</a>.",
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  ).launch()