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Update app.py
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app.py
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@@ -1,6 +1,6 @@
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import gradio as gr
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from PIL import Image
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from tld.denoiser import Denoiser
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from tld.diffusion import DiffusionGenerator
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@@ -19,10 +19,13 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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to_pil = transforms.ToPILImage()
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@torch.no_grad()
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def encode_text(label, model):
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@@ -55,6 +58,14 @@ def generate_image_from_text(prompt, class_guidance=6, seed=11, num_imgs=1, img_
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print("Images Generated and Saved. They will shortly output below.")
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return out
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denoiser = Denoiser(image_size=32, noise_embed_dims=256, patch_size=2,
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@@ -85,4 +96,4 @@ iface = gr.Interface(
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# Launch the app
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iface.launch()
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import gradio as gr
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from PIL import Image
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import requests
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from tld.denoiser import Denoiser
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from tld.diffusion import DiffusionGenerator
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to_pil = transforms.ToPILImage()
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def download_file(url, filename):
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with requests.get(url, stream=True) as r:
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r.raise_for_status()
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with open(filename, 'wb') as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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@torch.no_grad()
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def encode_text(label, model):
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print("Images Generated and Saved. They will shortly output below.")
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return out
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###config:
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vae_scale_factor = 8
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img_size = 32
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model_dtype = torch.float32
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file_url = "https://huggingface.co/apapiu/small_ldt/resolve/main/state_dict_378000.pth"
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local_filename = "state_dict_378000.pth"
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download_file(file_url, local_filename)
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denoiser = Denoiser(image_size=32, noise_embed_dims=256, patch_size=2,
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)
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# Launch the app
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iface.launch()
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