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3c7cefd
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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 <[email protected]>
app.py
CHANGED
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@@ -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/
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def predict(steps=1, seed=42):
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generator = torch.manual_seed(seed)
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@@ -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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gr.Interface(
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predict,
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inputs=[
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gr.inputs.Slider(1,
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gr.inputs.Slider(0,
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],
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outputs="
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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()
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