Spaces:
Running
on
Zero
Running
on
Zero
chore: fix dtype, etc
Browse files- .gitignore +3 -0
- app.py +16 -7
- requirements.txt +1 -1
.gitignore
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.env
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__pycache__
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.DS_Store
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app.py
CHANGED
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import random
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import numpy as np
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import torch
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from diffusers import StableDiffusionXLPipeline
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import spaces
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import gradio as gr
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from
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torch.backends.cuda.matmul.allow_tf32 = True
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torch.backends.cudnn.allow_tf32 = True
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device = "cuda"
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model_repo_id = "cagliostrolab/animagine-xl-4.0" # Replace to the model you would like to use
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@@ -44,7 +45,7 @@ def infer(
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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generator = torch.Generator().manual_seed(seed)
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latents = torch.randn(
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(
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def color_name_to_channels(color_name: str) -> list[int]:
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if color_name in COLOR_SET_MAP:
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return COLOR_SET_MAP[color_name]
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else:
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raise ValueError(f"Unknown color name: {color_name}")
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with gr.Blocks() as demo:
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with gr.Column():
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gr.Markdown(
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with gr.Row():
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prompt = gr.Text(
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label="Negative prompt",
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max_lines=1,
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placeholder="Enter a negative prompt",
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)
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seed = gr.Slider(
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import spaces # import first
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import random
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import numpy as np
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import torch
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from diffusers import StableDiffusionXLPipeline
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import gradio as gr
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from tkg import apply_tkg_noise, ColorSet, COLOR_SET_MAP
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torch.backends.cuda.matmul.allow_tf32 = True
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torch.backends.cudnn.allow_tf32 = True
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device = "cuda"
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model_repo_id = "cagliostrolab/animagine-xl-4.0" # Replace to the model you would like to use
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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generator = torch.Generator(device=device).manual_seed(seed)
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latents = torch.randn(
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(
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def color_name_to_channels(color_name: str) -> list[int]:
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if color_name in COLOR_SET_MAP:
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return COLOR_SET_MAP[color_name].channels
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else:
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raise ValueError(f"Unknown color name: {color_name}")
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with gr.Blocks() as demo:
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with gr.Column():
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gr.Markdown(
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"""
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# TKG Chroma-Key with AnimagineXL 4.0
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TKG-DMπ₯π: Training-free Chroma Key Content Generation Diffusion Model
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- arXiv: https://arxiv.org/abs/2411.15580
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- GitHub: https://github.com/ryugo417/TKG-DM
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""")
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with gr.Row():
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prompt = gr.Text(
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label="Negative prompt",
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max_lines=1,
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placeholder="Enter a negative prompt",
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value="lowres, bad anatomy, bad hands, text, error, missing finger, extra digits, fewer digits, cropped, worst quality, low quality, low score, bad score, average score, signature, watermark, username, blurry",
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)
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seed = gr.Slider(
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requirements.txt
CHANGED
@@ -3,4 +3,4 @@ diffusers
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torch
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transformers
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xformers
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spaces
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torch
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transformers
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xformers
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spaces>=0.40.1
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