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| import gradio as gr | |
| import sys | |
| # sys.path.append("LaVi-Bridge/test") | |
| # from llama2_unet_diffusion_lens import call_diffusion_lens | |
| from diffusion_lens import get_images | |
| import os | |
| import subprocess | |
| def prepare_images(images): | |
| return images | |
| # def call_diffusion_lens(prompt): | |
| # # os.chdir('LaVi-Bridge/test') | |
| # command = f"python -u llama2_unet.py --ckpt_dir 'LaVi-Bridge/llama2_unet' --output_dir 'output' --llama2_dir 'meta-llama/Llama-2-7b-hf' --prompt '{prompt}'" | |
| # subprocess.run(command, shell=True) | |
| # return 'output' | |
| def get_prompt(prompt): | |
| print('prompt:', prompt) | |
| print('calling diffusion lens') | |
| # parser.add_argument("--ckpt_dir", type=str, default="") | |
| # parser.add_argument("--output_dir", type=str, default="") | |
| # parser.add_argument("--llama2_dir", type=str, default="") | |
| # parser.add_argument("--prompts_path", type=str, default="inputs/in.txt") | |
| # parser.add_argument("--use_chat", action="store_true") | |
| # parser.add_argument("--generate_text", action="store_true") | |
| # parser.add_argument("--dont_use_lora", action="store_true") | |
| # parser.add_argument("--is_gradio", action="store_true") | |
| # args = { | |
| # 'ckpt_dir': 'LaVi-Bridge/LaVi-Bridge/llama2_unet', | |
| # 'output_dir': 'output', | |
| # 'llama2_dir': 'meta-llama/Llama-2-7b-hf', | |
| # 'prompt': prompt, | |
| # 'use_chat': False, | |
| # 'generate_text': False, | |
| # 'dont_use_lora': False, | |
| # 'is_gradio': True, | |
| # 'prompts_path': None | |
| # } | |
| # images = call_diffusion_lens(args, prompt) | |
| # print('done calling diffusion lens') | |
| # print('number of images:', len(images)) | |
| # images = prepare_images(images) | |
| # print('done preparing images') | |
| image = get_images(prompt) | |
| return image | |
| if __name__ == '__main__': | |
| print('starting') | |
| get_prompt("A photo of a cat") | |
| print('done') | |
| # iface = gr.Interface(fn=get_prompt, inputs="text", outputs="image", title="Diffusion Lens") | |
| # iface.launch() | |
| import gradio as gr | |
| def display_images(images): | |
| # Prepare images for display | |
| return [gr.Image(image) for image in images] | |
| if __name__ == '__main__': | |
| with gr.Blocks() as demo: | |
| gallery = gr.Gallery( | |
| label="Generated images", show_label=False, elem_id="gallery", | |
| columns=[1], rows=[1], object_fit="contain", height="auto") | |
| btn = gr.Button("Generate images", scale=0) | |
| btn.click(get_prompt, 'text', gallery) | |
| demo.launch() | |