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| import gradio as gr | |
| import os, pandas as pd | |
| from transformers import pipeline, set_seed | |
| import random, re | |
| import sys | |
| from pathlib import Path | |
| # read models from csv and init | |
| models = [r for idx,r in pd.read_csv('models.csv').iterrows()] | |
| current_model = models[0] | |
| # pipeline and core fncn for prompt generation | |
| gpt2_pipe = pipeline('text-generation', model='Gustavosta/MagicPrompt-Stable-Diffusion', tokenizer='gpt2') | |
| with open("ideas.txt", "r") as f: | |
| line = f.readlines() | |
| def generate(starting_text): | |
| seed = random.randint(100, 1000000) | |
| set_seed(seed) | |
| if starting_text == "": | |
| starting_text: str = line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize() | |
| starting_text: str = re.sub(r"[,:\-–.!;?_]", '', starting_text) | |
| response = gpt2_pipe(starting_text, max_length=(len(starting_text) + random.randint(60, 90)), num_return_sequences=4) | |
| response_list = [] | |
| for x in response: | |
| resp = x['generated_text'].strip() | |
| if resp != starting_text and len(resp) > (len(starting_text) + 4) and resp.endswith((":", "-", "—")) is False: | |
| response_list.append(resp+'\n') | |
| response_end = "\n".join(response_list) | |
| response_end = re.sub('[^ ]+\.[^ ]+','', response_end) | |
| response_end = response_end.replace("<", "").replace(">", "") | |
| if response_end != "": | |
| return response_end | |
| examples = [] | |
| for x in range(8): | |
| examples.append(line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize()) | |
| # text_gen = gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion_link") | |
| models2 = [] #can improve this, no need to load and keep all models in memory, increases cpu usage + latency | |
| for model in models: | |
| model_url = f"models/{model['url']}" | |
| loaded_model = gr.Interface.load(model_url, live=True, preprocess=True) | |
| models2.append(loaded_model) | |
| def text_it(inputs,text_gen=generate): | |
| return text_gen(inputs).split('\n\n')[0] | |
| def set_model(current_model_index): | |
| global current_model | |
| current_model = models[current_model_index] | |
| return gr.update(value=f"{current_model['name']}") | |
| def send_it(inputs, model_choice): | |
| proc = models2[model_choice] | |
| return proc(inputs) | |
| with gr.Blocks() as myface: | |
| gr.HTML() | |
| with gr.Row(): | |
| with gr.Row(): | |
| input_text = gr.Textbox(label="Prompt idea", lines=1) | |
| # Model selection dropdown | |
| model_name1 = gr.Dropdown( | |
| label="Choose Model", | |
| choices=[m["name"] for m in models], | |
| type="index", | |
| value=current_model["name"], | |
| interactive=True, | |
| ) | |
| with gr.Row(): | |
| see_prompts = gr.Button("Step 1 - Generate Prompts", variant="primary") | |
| run = gr.Button("Step 2 - Generate Images", variant="primary") | |
| with gr.Row(): | |
| output1 = gr.Image(label="") | |
| output2 = gr.Image(label="") | |
| output3 = gr.Image(label="") | |
| with gr.Row(): | |
| magic1 = gr.Textbox(label="Generated Prompt", lines=2) | |
| magic2 = gr.Textbox(label="Generated Prompt", lines=2) | |
| magic3 = gr.Textbox(label="Generated Prompt", lines=2) | |
| with gr.Row(): | |
| output4 = gr.Image(label="") | |
| output5 = gr.Image(label="") | |
| output6 = gr.Image(label="") | |
| with gr.Row(): | |
| magic4 = gr.Textbox(label="Generated Prompt", lines=2) | |
| magic5 = gr.Textbox(label="Generated Prompt", lines=2) | |
| magic6 = gr.Textbox(label="Generated Prompt", lines=2) | |
| with gr.Row(): | |
| output7 = gr.Image(label="") | |
| output8 = gr.Image(label="") | |
| output9 = gr.Image(label="") | |
| with gr.Row(): | |
| magic7 = gr.Textbox(label="Generated Prompt", lines=2) | |
| magic8 = gr.Textbox(label="Generated Prompt", lines=2) | |
| magic9 = gr.Textbox(label="Generated Prompt", lines=2) | |
| model_name1.change(set_model, inputs=model_name1, outputs=model_name1) | |
| run.click(send_it, inputs=[magic1, model_name1], outputs=[output1]) | |
| run.click(send_it, inputs=[magic2, model_name1], outputs=[output2]) | |
| run.click(send_it, inputs=[magic3, model_name1], outputs=[output3]) | |
| run.click(send_it, inputs=[magic4, model_name1], outputs=[output4]) | |
| run.click(send_it, inputs=[magic5, model_name1], outputs=[output5]) | |
| run.click(send_it, inputs=[magic6, model_name1], outputs=[output6]) | |
| run.click(send_it, inputs=[magic7, model_name1], outputs=[output7]) | |
| run.click(send_it, inputs=[magic8, model_name1], outputs=[output8]) | |
| run.click(send_it, inputs=[magic9, model_name1], outputs=[output9]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic1]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic2]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic3]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic4]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic5]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic6]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic7]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic8]) | |
| see_prompts.click(text_it, inputs=[input_text], outputs=[magic9]) | |
| myface.queue(concurrency_count=64) | |
| myface.launch(inline=True, show_api=False, max_threads=64) |