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Yaron Koresh
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -13,7 +13,8 @@ from pathos.threading import ThreadPool as Pool
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#from diffusers.utils import export_to_gif
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#from huggingface_hub import hf_hub_download
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#from safetensors.torch import load_file
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from diffusers import
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#import jax
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#import jax.numpy as jnp
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@@ -22,6 +23,11 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
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#pipe = FlaxStableDiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", dtype=jnp.bfloat16, token=os.getenv("hf_token")).to(device)
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pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16, revision="refs/pr/1", token=os.getenv("hf_token")).to(device)
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def translate(text,lang):
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if text == None or lang == None:
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@@ -81,7 +87,7 @@ def generate_random_string(length):
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return ''.join(random.choice(characters) for _ in range(length))
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@spaces.GPU(duration=35)
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def Piper(_do
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try:
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retu = pipe(
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_do,
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@@ -97,6 +103,18 @@ def Piper(_do,neg):
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print(e)
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return None
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@spaces.GPU(duration=25)
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def tok(txt):
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toks = pipe.tokenizer(txt)['input_ids']
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@@ -110,15 +128,24 @@ def infer(p1,p2):
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_do.append(f'{p1}')
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if p2 != "":
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_dont = f'{p2} where in {p1}'
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neg =
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else:
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neg = None
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output = Piper('A '+" ".join(_do)
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if output == None:
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return
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else:
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output.images[0].save(name)
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css="""
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input, input::placeholder {
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#from diffusers.utils import export_to_gif
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#from huggingface_hub import hf_hub_download
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#from safetensors.torch import load_file
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from diffusers import DiffusionPipeline, StableDiffusionXLImg2ImgPipeline
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from diffusers.utils import load_image
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#import jax
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#import jax.numpy as jnp
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#pipe = FlaxStableDiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", dtype=jnp.bfloat16, token=os.getenv("hf_token")).to(device)
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pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16, revision="refs/pr/1", token=os.getenv("hf_token")).to(device)
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pipe2 = StableDiffusionXLImg2ImgPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-refiner-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
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).to(device)
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pipe2.unet = torch.compile(pipe2.unet, mode="reduce-overhead", fullgraph=True)
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def translate(text,lang):
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if text == None or lang == None:
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return ''.join(random.choice(characters) for _ in range(length))
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@spaces.GPU(duration=35)
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def Piper(_do):
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try:
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retu = pipe(
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_do,
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print(e)
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return None
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@spaces.GPU(duration=75)
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def Piper2(name,neg):
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try:
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retu = pipe2(
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negative_prompt=neg,
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image=name
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)
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return retu
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except Exception as e:
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print(e)
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return None
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@spaces.GPU(duration=25)
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def tok(txt):
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toks = pipe.tokenizer(txt)['input_ids']
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_do.append(f'{p1}')
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if p2 != "":
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_dont = f'{p2} where in {p1}'
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neg = _dont
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else:
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neg = None
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output = Piper('A '+" ".join(_do))
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if output == None:
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return None
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else:
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output.images[0].save(name)
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if neg == None:
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return name
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init_image = load_image(name).convert("RGB")
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output2 = Piper2(init_image,neg)
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if output2 == None:
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return None
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else:
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output2.images[0].save("_"+name)
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return "_"+name
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css="""
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input, input::placeholder {
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