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lvmin 2023-08-10 07:02:41 -07:00
parent f83523f7b5
commit 0130cfd3b6
1 changed files with 14 additions and 24 deletions
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webui.py
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@ -1,30 +1,20 @@
import os import gradio as gr
import modules.core as core from modules.default_pipeline import process
from modules.path import modelfile_path
xl_base_filename = os.path.join(modelfile_path, 'sd_xl_base_1.0.safetensors') def generate_clicked(positive_prompt):
xl_refiner_filename = os.path.join(modelfile_path, 'sd_xl_refiner_1.0.safetensors') return process(positive_prompt=positive_prompt, negative_prompt='bad, ugly')
xl_base = core.load_model(xl_base_filename)
positive_conditions = core.encode_prompt_condition(clip=xl_base.clip, prompt='a beautiful woman in forest') block = gr.Blocks().queue()
negative_conditions = core.encode_prompt_condition(clip=xl_base.clip, prompt='bad, ugly') with block:
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Prompt", value='a handsome man in forest')
run_button = gr.Button(label="Run")
with gr.Column():
result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery").style(grid=2, height='auto')
run_button.click(fn=generate_clicked, inputs=[prompt], outputs=[result_gallery])
empty_latent = core.generate_empty_latent(width=1024, height=1024, batch_size=1)
sampled_latent = core.ksample( block.launch()
unet=xl_base.unet,
positive_condition=positive_conditions,
negative_condition=negative_conditions,
latent_image=empty_latent
)
decoded_latent = core.decode_vae(vae=xl_base.vae, latent_image=sampled_latent)
images = core.image_to_numpy(decoded_latent)
for image in images:
import cv2
cv2.imwrite('a.png', image[:, :, ::-1])