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Create app.py
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app.py
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import streamlit as st
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from io import BytesIO
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from typing import Literal
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from diffusers import StableDiffusionPipeline
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import torch
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import time
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seed = 42
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generator = torch.manual_seed(seed)
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NUM_ITERS_TO_RUN = 5
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NUM_INFERENCE_STEPS = 50
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NUM_IMAGES_PER_PROMPT = 2
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def text2image(
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prompt: str,
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repo_id: Literal[
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"dreamlike-art/dreamlike-photoreal-2.0",
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"hakurei/waifu-diffusion",
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"prompthero/openjourney",
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"stabilityai/stable-diffusion-2-1",
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"runwayml/stable-diffusion-v1-5",
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"nota-ai/bk-sdm-small",
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"CompVis/stable-diffusion-v1-4",
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],
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):
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start = time.time()
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if torch.cuda.is_available():
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print("Using GPU")
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pipeline = StableDiffusionPipeline.from_pretrained(
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repo_id,
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torch_dtype=torch.float16,
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use_safetensors=True,
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).to("cuda")
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else:
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print("Using CPU")
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pipeline = StableDiffusionPipeline.from_pretrained(
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repo_id,
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torch_dtype=torch.float32,
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use_safetensors=True,
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)
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for _ in range(NUM_ITERS_TO_RUN):
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images = pipeline(
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prompt,
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num_inference_steps=NUM_INFERENCE_STEPS,
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generator=generator,
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num_images_per_prompt=NUM_IMAGES_PER_PROMPT,
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).images
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end = time.time()
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return images[0], start, end
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def app():
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st.header("Text-to-image Web App")
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st.subheader("Powered by Hugging Face")
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user_input = st.text_area(
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"Enter your text prompt below and click the button to submit."
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)
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option = st.selectbox(
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"Select model (in order of processing time)",
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(
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"nota-ai/bk-sdm-small",
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"CompVis/stable-diffusion-v1-4",
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"runwayml/stable-diffusion-v1-5",
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"prompthero/openjourney",
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"hakurei/waifu-diffusion",
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"stabilityai/stable-diffusion-2-1",
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"dreamlike-art/dreamlike-photoreal-2.0",
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),
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)
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with st.form("my_form"):
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submit = st.form_submit_button(label="Submit text prompt")
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if submit:
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with st.spinner(text="Generating image ... It may take up to 20 minutes."):
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im, start, end = text2image(prompt=user_input, repo_id=option)
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buf = BytesIO()
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im.save(buf, format="PNG")
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byte_im = buf.getvalue()
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hours, rem = divmod(end - start, 3600)
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minutes, seconds = divmod(rem, 60)
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st.success(
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"Processing time: {:0>2}:{:0>2}:{:05.2f}.".format(
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int(hours), int(minutes), seconds
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)
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)
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st.image(im)
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st.download_button(
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label="Click here to download",
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data=byte_im,
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file_name="generated_image.png",
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mime="image/png",
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)
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if __name__ == "__main__":
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app()
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