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import gradio as gr | |
# import os | |
# import sys | |
# from pathlib import Path | |
import time | |
models =[ | |
"stephanebhiri/lora-trained-xl-colab-hya13", | |
"stablediffusionapi/icon-lab-ai", | |
"stephanebhiri/lora-trained-xl-colab-stp17", | |
"Yntec/DreamLikeRemix", | |
"stephanebhiri/lora-trained-xl-colab-stp16", | |
"slakshmi/my-pet-dog-xzg", | |
"kabachuha/maxwell-the-cat-diffusion", | |
"stablediffusionapi/jueduixianshi", | |
"AP123/eapt-3sn6-u0ch", | |
] | |
model_functions = {} | |
model_idx = 1 | |
for model_path in models: | |
try: | |
model_functions[model_idx] = gr.Interface.load(f"models/{model_path}", live=False, preprocess=True, postprocess=False) | |
except Exception as error: | |
def the_fn(txt): | |
return None | |
model_functions[model_idx] = gr.Interface(fn=the_fn, inputs=["text"], outputs=["image"]) | |
model_idx+=1 | |
def send_it_idx(idx): | |
def send_it_fn(prompt): | |
output = (model_functions.get(str(idx)) or model_functions.get(str(1)))(prompt) | |
return output | |
return send_it_fn | |
def get_prompts(prompt_text): | |
return prompt_text | |
def clear_it(val): | |
if int(val) != 0: | |
val = 0 | |
else: | |
val = 0 | |
pass | |
return val | |
def all_task_end(cnt,t_stamp): | |
to = t_stamp + 60 | |
et = time.time() | |
if et > to and t_stamp != 0: | |
d = gr.update(value=0) | |
tog = gr.update(value=1) | |
#print(f'to: {to} et: {et}') | |
else: | |
if cnt != 0: | |
d = gr.update(value=et) | |
else: | |
d = gr.update(value=0) | |
tog = gr.update(value=0) | |
#print (f'passing: to: {to} et: {et}') | |
pass | |
return d, tog | |
def all_task_start(): | |
print("\n\n\n\n\n\n\n") | |
t = time.gmtime() | |
t_stamp = time.time() | |
current_time = time.strftime("%H:%M:%S", t) | |
return gr.update(value=t_stamp), gr.update(value=t_stamp), gr.update(value=0) | |
def clear_fn(): | |
nn = len(models) | |
return tuple([None, *[None for _ in range(nn)]]) | |
with gr.Blocks(title="SD Models") as my_interface: | |
with gr.Column(scale=12): | |
# with gr.Row(): | |
# gr.Markdown("""- Primary prompt: 你想画的内容(英文单词,如 a cat, 加英文逗号效果更好;点 Improve 按钮进行完善)\n- Real prompt: 完善后的提示词,出现后再点右边的 Run 按钮开始运行""") | |
with gr.Row(): | |
with gr.Row(scale=6): | |
primary_prompt=gr.Textbox(label="Prompt", value="") | |
# real_prompt=gr.Textbox(label="Real prompt") | |
with gr.Row(scale=6): | |
# improve_prompts_btn=gr.Button("Improve") | |
with gr.Row(): | |
run=gr.Button("Run",variant="primary") | |
clear_btn=gr.Button("Clear") | |
with gr.Row(): | |
sd_outputs = {} | |
model_idx = 1 | |
for model_path in models: | |
with gr.Column(scale=3, min_width=320): | |
with gr.Box(): | |
sd_outputs[model_idx] = gr.Image(label=model_path) | |
pass | |
model_idx += 1 | |
pass | |
pass | |
with gr.Row(visible=False): | |
start_box=gr.Number(interactive=False) | |
end_box=gr.Number(interactive=False) | |
tog_box=gr.Textbox(value=0,interactive=False) | |
start_box.change( | |
all_task_end, | |
[start_box, end_box], | |
[start_box, tog_box], | |
every=1, | |
show_progress=False) | |
primary_prompt.submit(all_task_start, None, [start_box, end_box, tog_box]) | |
run.click(all_task_start, None, [start_box, end_box, tog_box]) | |
runs_dict = {} | |
model_idx = 1 | |
for model_path in models: | |
runs_dict[model_idx] = run.click(model_functions[model_idx], inputs=[primary_prompt], outputs=[sd_outputs[model_idx]]) | |
model_idx += 1 | |
pass | |
pass | |
# improve_prompts_btn_clicked=improve_prompts_btn.click( | |
# get_prompts, | |
# inputs=[primary_prompt], | |
# outputs=[primary_prompt], | |
# cancels=list(runs_dict.values())) | |
clear_btn.click( | |
clear_fn, | |
None, | |
[primary_prompt, *list(sd_outputs.values())], | |
cancels=[*list(runs_dict.values())]) | |
tog_box.change( | |
clear_it, | |
tog_box, | |
tog_box, | |
cancels=[*list(runs_dict.values())]) | |
my_interface.queue(concurrency_count=600, status_update_rate=1) | |
my_interface.launch(inline=True, show_api=False) | |