Define the object's region.
Using the following formula as default: w = scale * token_weight_martix * sigma * std(qk).
"""
)
with gr.Row():
with gr.Column(scale=55):
formula_button = gr.Dropdown(
choices=[k[0] for k in formula],
label="Formual",
value=formula[0][0],
)
rendered = gr.Image(
invert_colors=True,
source="canvas",
interactive=False,
image_mode="RGBA",
)
with gr.Column(scale=45):
with gr.Group():
with gr.Row():
with gr.Column(scale=70):
# g_strength = gr.Slider(
# label="Compliance rate",
# minimum=0,
# maximum=2,
# step=0.01,
# value=0.4,
# )
text = gr.Textbox(
lines=2,
interactive=True,
label="Token to Draw: (Separate by comma)",
)
radio = gr.Radio([], label="Tokens",visible = False)
sk_update = gr.Button(value="Update").style(
rounded=(False, True, True, False)
)
# g_strength.change(lambda b: gr.update(f"Scaled additional attn: $w = {b} \log (1 + \sigma) \std (Q^T K)$."), inputs=g_strength, outputs=[g_output])
with gr.Tab("SketchPad"):
sp = gr.Image(
width = 512,
height = 512,
image_mode="L",
tool="sketch",
source="canvas",
interactive=False
)
'''mask_outsides = gr.Checkbox(
label="Mask other areas",
value=False
)'''
with gr.Row():
mask_outsides = gr.Slider(
label="Decrease unmarked region weight",
minimum=0,
maximum=3,
step=0.01,
value=0,
)
strength = gr.Slider(
label="Token-Region strength",
minimum=0,
maximum=3,
step=0.01,
value=0.5,
)
width.change(
apply_size_sketch,
inputs=[width, height,global_stats,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[global_stats, rendered,sp],
queue=False,
)
height.change(
apply_size_sketch,
inputs=[width, height,global_stats,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[global_stats, rendered,sp],
queue=False,
)
inf_image.change(
apply_size_sketch,
inputs=[width, height,global_stats,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[global_stats, rendered,sp],
queue=False,
)
sk_update.click(
detect_text,
inputs=[text, global_stats, width, height,formula_button,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[global_stats, sp, radio, rendered,formula_button],
queue=False,
)
radio.change(
switch_canvas,
inputs=[radio, global_stats, width, height,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[sp, strength, mask_outsides, rendered],
queue=False,
)
sp.edit(
apply_canvas,
inputs=[radio, sp, global_stats, width, height,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[global_stats, rendered],
queue=False,
)
strength.change(
apply_weight,
inputs=[radio, strength, global_stats],
outputs=[global_stats],
queue=False,
)
mask_outsides.change(
apply_option,
inputs=[radio, mask_outsides, global_stats],
outputs=[global_stats],
queue=False,
)
with gr.Tab("UploadFile"):
sp2 = gr.Image(
image_mode="RGB",
source="upload",
)
sp3 = gr.Image(
image_mode="L",
source="canvas",
visible = False,
interactive = False,
)
with gr.Row():
previous_page = gr.Button(value="Previous",visible = False,)
next_page = gr.Button(value="Next",visible = False,)
'''mask_outsides2 = gr.Checkbox(
label="Mask other areas",
value=False,
)'''
with gr.Row():
mask_outsides2 = gr.Slider(
label="Decrease unmarked region weight",
minimum=0,
maximum=3,
step=0.01,
value=0,
)
strength2 = gr.Slider(
label="Token-Region strength",
minimum=0,
maximum=3,
step=0.01,
value=0.5,
)
'''sk_update.click(
detect_text1,
inputs=[text, global_stats, width, height,formula_button,inf_image],
outputs=[global_stats, radio, rendered,formula_button],
queue=False,
)'''
with gr.Row():
apply_style = gr.Button(value="Apply")
apply_clustering_style = gr.Button(value="Extracting color regions")
with gr.Row():
add_style = gr.Button(value="Apply",visible = False)
complete_clustering = gr.Button(value="Complete",visible = False)
apply_style.click(
apply_image,
inputs=[sp2, radio, width, height, strength2, mask_outsides2, global_stats,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[global_stats, rendered],
queue=False,
)
apply_clustering_style.click(
apply_base_on_color,
inputs=[sp2,global_stats,width, height,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[rendered,apply_style,apply_clustering_style,previous_page,next_page,complete_clustering,sp2,sp3,add_style,global_stats],
queue=False,
)
previous_page.click(
previous_image_page,
inputs=[sp3],
outputs=[sp3],
queue=False,
)
next_page.click(
next_image_page,
inputs=[sp3],
outputs=[sp3],
queue=False,
)
add_style.click(
apply_image_clustering,
inputs=[sp3, radio, width, height, strength2, mask_outsides2, global_stats,inf_image,inpaiting_mode,inf_image_inpaiting],
outputs=[global_stats,rendered],
queue=False,
)
complete_clustering.click(
completing_clustering,
inputs=[sp2],
outputs=[apply_style,apply_clustering_style,previous_page,next_page,complete_clustering,sp2,sp3,add_style],
queue=False,
)
'''width.change(
apply_new_res,
inputs=[width, height, global_stats,inf_image,rendered],
outputs=[global_stats, rendered],
queue=False,
)
height.change(
apply_new_res,
inputs=[width, height, global_stats,inf_image,rendered],
outputs=[global_stats, rendered],
queue=False,
)'''
# color_stats = gr.State(value={})
# text.change(detect_color, inputs=[sp, text, color_stats], outputs=[color_stats, rendered])
# sp.change(detect_color, inputs=[sp, text, color_stats], outputs=[color_stats, rendered])
inputs = [
prompt,
guidance,
steps,
width,
height,
clip_skip,
seed,
neg_prompt,
global_stats,
#g_strength,
inf_image,
inf_strength,
hr_enabled,
hr_method,
hr_scale,
hr_denoise,
sampler,
ti_state,
model,
lora_group,
#lora_vals,
#lora_scale,
formula_button,
controlnet_enabled,
model_control_net,
low_threshold,
high_threshold,
has_body_openpose,
has_hand_openpose,
has_face_openpose,
controlnet_img,
image_condition,
controlnet_scale,
preprocessor_name,
diffuser_pipeline,
sampler_hires,
latent_processing,
control_guidance_start,
control_guidance_end,
multi_controlnet,
disable_preprocessing,
region_condition,
hr_process_enabled,
ip_adapter,
model_ip_adapter,
inf_adapt_image,
inf_adapt_image_strength,
hr_region_condition,
adapter_enabled,
model_adapter,
low_threshold_adapter,
high_threshold_adapter,
has_body_openpose_adapter,
has_hand_openpose_adapter,
has_face_openpose_adapter,
adapter_img,
image_condition_adapter,
preprocessor_adapter,
adapter_conditioning_scale,
adapter_conditioning_factor,
multi_adapter,
disable_preprocessing_adapter,
ip_adapter_multi,
guidance_rescale,
inf_control_adapt_image,
long_encode,
inpaiting_mode,
invert_mask_mode,
mask_upload,
inf_image_inpaiting,
invert_ip_adapter_mask_mode,
vae_used,
]
outputs = [image_out,gallery]
prompt.submit(inference, inputs=inputs, outputs=outputs)
generate.click(inference, inputs=inputs, outputs=outputs)
print(f"Space built in {time.time() - start_time:.2f} seconds")
#demo.queue().launch(share=True,debug=True)
demo.launch(enable_queue=True, server_name="0.0.0.0", server_port=7860)