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| from __future__ import annotations | |
| from os import pipe | |
| import gradio as gr | |
| import numpy as np | |
| from model import Model | |
| from diffusers import StableDiffusionPipeline | |
| import gradio as gr | |
| from story_generator import StoryGenerator | |
| import torch | |
| TITLE = '' | |
| DESCRIPTION = '''# StyleGAN3 | |
| This is an unofficial demo for [https://github.com/NVlabs/stylegan3](https://github.com/NVlabs/stylegan3). | |
| ''' | |
| model = Model() | |
| model_id = "runwayml/stable-diffusion-v1-5" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) | |
| pipe = pipe.to("cuda") # Remove or comment out this line if using CPU | |
| sg = None | |
| with gr.Blocks(css='style.css') as image_gen_block: | |
| gr.Markdown(DESCRIPTION) | |
| with gr.Tabs(): | |
| with gr.TabItem('Character'): | |
| with gr.Row(): | |
| with gr.Column(): | |
| model_name = gr.Dropdown(list(model.MODEL_NAME_DICT.keys()), | |
| value='FemaleHero-256-T', | |
| label='Model') | |
| seed = gr.Slider(0, | |
| np.iinfo(np.uint32).max, | |
| step=1, | |
| value=0, | |
| label='Seed') | |
| psi = gr.Slider(0, | |
| 2, | |
| step=0.05, | |
| value=0.7, | |
| label='Truncation psi') | |
| tx = gr.Slider(-1, | |
| 1, | |
| step=0.05, | |
| value=0, | |
| label='Translate X') | |
| ty = gr.Slider(-1, | |
| 1, | |
| step=0.05, | |
| value=0, | |
| label='Translate Y') | |
| angle = gr.Slider(-180, | |
| 180, | |
| step=5, | |
| value=0, | |
| label='Angle') | |
| run_button = gr.Button('Run') | |
| with gr.Column(): | |
| result = gr.Image(label='Result', elem_id='result') | |
| # City generation tab | |
| with gr.TabItem('City'): | |
| with gr.Row(): | |
| generate_city_button = gr.Button("Generate City") | |
| with gr.Row(): | |
| city_output = gr.Image(label="Generated City", elem_id="city_output") | |
| with gr.TabItem('Story'): | |
| with gr.Row(): | |
| api_key_input_sg = gr.Textbox(label="OpenAI API Key") | |
| prompt_input = gr.Textbox(label='Prompt') | |
| generate_button = gr.Button('Generate Story') | |
| with gr.Row(): | |
| story_output = gr.Textbox(label='Generated Story', | |
| placeholder='Click "Generate Story" to see the story', | |
| readonly=True) | |
| def generate_story(prompt, api_key): | |
| sg = StoryGenerator(api_key) | |
| return sg.generate_story(prompt) | |
| def generate_city(): | |
| model_id = "runwayml/stable-diffusion-v1-5" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) | |
| pipe = pipe.to("cuda") | |
| city_prompt = f"A metropolis city, HD" | |
| city_image = pipe(city_prompt).images[0] | |
| return city_image | |
| generate_city_button.click(fn=generate_city, inputs=None, outputs=city_output) | |
| model_name.change(fn=model.set_model, inputs=model_name, outputs=None) | |
| run_button.click(fn=model.generate_image, | |
| inputs=[ | |
| model_name, | |
| seed, | |
| psi, | |
| tx, | |
| ty, | |
| angle, | |
| ], | |
| outputs=result) | |
| generate_button.click(fn=generate_story, inputs=[prompt_input, api_key_input_sg], outputs=story_output) | |
| image_gen_block.queue().launch(show_api=False) | |