Spaces:
Runtime error
Runtime error
File size: 3,432 Bytes
a660631 f521e88 a660631 84448a9 a660631 f521e88 a660631 c637e71 f521e88 d5479f6 f521e88 d5479f6 f521e88 a660631 f521e88 a660631 f521e88 a660631 f521e88 c637e71 a660631 c637e71 a660631 ae34a8d 3c4344e a660631 3c4344e a660631 c637e71 a660631 ae34a8d 3c4344e a660631 f521e88 a660631 c637e71 a660631 f521e88 a660631 f521e88 a660631 |
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 |
#!/usr/bin/env python
import gradio as gr
from settings import (
DEFAULT_IMAGE_RESOLUTION,
DEFAULT_NUM_IMAGES,
MAX_IMAGE_RESOLUTION,
MAX_NUM_IMAGES,
MAX_SEED,
)
from utils import randomize_seed_fn
def create_demo(process):
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
image = gr.Image()
prompt = gr.Textbox(label="Prompt")
run_button = gr.Button("Run")
with gr.Accordion("Advanced options", open=False):
preprocessor_name = gr.Radio(
label="Preprocessor", choices=["Midas", "DPT", "None"], value="DPT"
)
num_samples = gr.Slider(
label="Number of images", minimum=1, maximum=MAX_NUM_IMAGES, value=DEFAULT_NUM_IMAGES, step=1
)
image_resolution = gr.Slider(
label="Image resolution",
minimum=256,
maximum=MAX_IMAGE_RESOLUTION,
value=DEFAULT_IMAGE_RESOLUTION,
step=256,
)
preprocess_resolution = gr.Slider(
label="Preprocess resolution", minimum=128, maximum=512, value=384, step=1
)
num_steps = gr.Slider(label="Number of steps", minimum=1, maximum=100, value=20, step=1)
guidance_scale = gr.Slider(label="Guidance scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1)
seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
a_prompt = gr.Textbox(label="Additional prompt", value="best quality, extremely detailed")
n_prompt = gr.Textbox(
label="Negative prompt",
value="longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
)
with gr.Column():
result = gr.Gallery(label="Output", show_label=False, columns=2, object_fit="scale-down")
inputs = [
image,
prompt,
a_prompt,
n_prompt,
num_samples,
image_resolution,
preprocess_resolution,
num_steps,
guidance_scale,
seed,
preprocessor_name,
]
prompt.submit(
fn=randomize_seed_fn,
inputs=[seed, randomize_seed],
outputs=seed,
queue=False,
api_name=False,
).then(
fn=process,
inputs=inputs,
outputs=result,
api_name=False,
)
run_button.click(
fn=randomize_seed_fn,
inputs=[seed, randomize_seed],
outputs=seed,
queue=False,
api_name=False,
).then(
fn=process,
inputs=inputs,
outputs=result,
api_name="depth",
)
return demo
if __name__ == "__main__":
from model import Model
model = Model(task_name="depth")
demo = create_demo(model.process_depth)
demo.queue().launch()
|