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import gradio as gr
import os
from pathlib import Path
from PIL import Image
root = Path(os.path.dirname(__file__))
def infer(
text,
guidance_scale,
):
img = (
Image.open(root / "cheetah.jpg")
if text == "Cheetah"
else Image.open(root / "frog.jpg")
)
img = img.resize((224, 224))
return ([img, img, img, img], "image")
block = gr.Blocks()
examples = [
["A serious capybara at work, wearing a suit", 7],
["A Squirtle fine dining with a view to the London Eye", 7],
["A tamale food cart in front of a Japanese Castle", 7],
["a graffiti of a robot serving meals to people", 7],
["a beautiful cabin in Attersee, Austria, 3d animation style", 7],
]
with block as demo:
with gr.Row(elem_id="prompt-container", equal_height=True):
text = gr.Textbox(
label="Enter your prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
elem_id="prompt-text-input",
)
gallery = gr.Gallery(
label="Generated images", show_label=False, elem_id="gallery", rows=2, columns=2
)
out_txt = gr.Textbox(
label="Prompt",
placeholder="Enter a prompt to generate an image",
lines=3,
elem_id="prompt-text-input",
)
guidance_scale = gr.Slider(
label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
)
ex = gr.Examples(
examples=examples,
fn=infer,
inputs=[text, guidance_scale],
outputs=[gallery, out_txt],
cache_examples=True,
)
text.submit(
infer,
inputs=[text, guidance_scale],
outputs=[gallery, out_txt],
concurrency_id="infer",
concurrency_limit=8,
)
with gr.Blocks() as demo:
block.render()
if __name__ == "__main__":
demo.queue(max_size=10, api_open=False).launch(show_api=False)
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