Spaces:
Runtime error
Runtime error
File size: 3,679 Bytes
1487e43 11d8a12 1487e43 11d8a12 1487e43 11d8a12 1487e43 11d8a12 39c626a 11d8a12 67fea0c 39c626a 11d8a12 cccff19 39c626a 11d8a12 1487e43 cccff19 11d8a12 1487e43 11d8a12 1487e43 11d8a12 1487e43 ac66580 1487e43 11d8a12 1487e43 11d8a12 1487e43 489d3ca 1487e43 489d3ca 1487e43 11d8a12 1487e43 11d8a12 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 |
import gradio as gr
import numpy as np
from optimum.intel import OVStableDiffusionPipeline, OVStableDiffusionXLPipeline, OVLatentConsistencyModelPipeline
from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
from diffusers import DiffusionPipeline
#model_id = "echarlaix/sdxl-turbo-openvino-int8"
#model_id = "echarlaix/LCM_Dreamshaper_v7-openvino"
#model_id = "OpenVINO/LCM_Dreamshaper_v7-int8-ov"
model_id = "stabilityai/stable-diffusion-xl-base-1.0"
#safety_checker = StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker")
#pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, compile=False, safety_checker=safety_checker)
#pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, compile=False)
pipeline = OVStableDiffusionXLPipeline.from_pretrained(model_id)
batch_size, num_images, height, width = 1, 1, 256, 256
#pipeline.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)
#pipeline.load_textual_inversion("./badhandv4.pt", "badhandv4")
#hiten1
#pipeline.load_textual_inversion("./hiten1.pt", "hiten1")
#pipeline.compile()
#TypeError: LatentConsistencyPipelineMixin.__call__() got an unexpected keyword argument 'negative_prompt'
negative_prompt="easynegative,bad anatomy, bad hands, missing fingers, extra fingers, three hands, three legs, bad arms, missing legs, missing arms, poorly drawn face, bad face, fused face, cloned face, three crus, fused feet, fused thigh, extra crus, ugly fingers, horn, cartoon, cg, 3d, unreal, animate, amputation, disconnected limbs, nsfw, nude, censored, "
def infer(prompt, num_inference_steps):
image = pipeline(
prompt = prompt,
negative_prompt = negative_prompt,
guidance_scale = 7.0,
num_inference_steps = num_inference_steps,
width = width,
height = height,
num_images_per_prompt=num_images,
).images[0]
return image
examples = [
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
"An astronaut riding a green horse",
"A delicious ceviche cheesecake slice",
]
css="""
#col-container {
margin: 0 auto;
max-width: 520px;
}
"""
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(f"""
# Demo :stabilityai/stable-diffusion-xl-base-1.0 OVStableDiffusionXLPipeline(fail sample)
""")
with gr.Row():
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
container=False,
)
run_button = gr.Button("Run", scale=0)
result = gr.Image(label="Result", show_label=False)
with gr.Accordion("Advanced Settings", open=False):
#with gr.Row():
# negative_prompt = gr.Text(
# label="Negative prompt",
# max_lines=1,
# placeholder="Enter a negative prompt",
# )
with gr.Row():
num_inference_steps = gr.Slider(
label="Number of inference steps",
minimum=1,
maximum=30,
step=1,
value=28,
)
gr.Examples(
examples = examples,
inputs = [prompt]
)
run_button.click(
fn = infer,
inputs = [prompt, num_inference_steps],
outputs = [result]
)
demo.queue().launch(share=True) |