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| import gradio as gr | |
| import requests | |
| import os | |
| import torch as th | |
| from torch import autocast | |
| from diffusers import StableDiffusionPipeline | |
| HF_TOKEN = os.environ["HF_TOKEN"] | |
| #HF_TOKEN = os.environ.get("diffuse_new") or True | |
| has_cuda = th.cuda.is_available() | |
| device = th.device('cpu' if not th.cuda.is_available() else 'cuda') | |
| print(f"device is :{device}") | |
| # init stable diffusion model | |
| #pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=th.float32, use_auth_token= HF_TOKEN).to(device) #revision="fp16", | |
| def get_sd_old(translated_txt): | |
| scale=7.5 | |
| steps=45 | |
| with autocast('cpu' if not th.cuda.is_available() else 'cuda'): | |
| image = pipe(translated_txt, guidance_scale=scale, num_inference_steps=steps)["sample"][0] | |
| return image | |
| #API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom" | |
| #HF_TOKEN = os.environ.get("diffuse_new") or True | |
| #headers = {"Authorization": f"Bearer {HF_TOKEN}"} | |
| sd_inf = gr.Interface.load(name="spaces/stabilityai/stable-diffusion", api_key = HF_TOKEN, use_auth_token=HF_TOKEN )#'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') | |
| def get_sd(translated_txt): | |
| print("******** Inside get_SD ********") | |
| print(f"translated_txt is : {translated_txt}") | |
| #sd_inf = gr.Blocks.load(name="spaces/stabilityai/stable-diffusion", use_auth_token='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') | |
| print(f"stable Diff inf is : {sd_inf}") | |
| sd_img_gallery = sd_inf(translated_txt, float(4),float(45), float(7.5),1024, fn_index=2) # fn_index=2)[0] #(prompt, samples, steps, scale, seed) #translated_txt | |
| return sd_img_gallery[0] | |
| demo = gr.Blocks() | |
| with demo: | |
| gr.Markdown("Testing Diffusion models. STILL VERY MUCH WORK IN PROGRESS !!!!!!!!") | |
| with gr.Row(): | |
| in_text_prompt = gr.Textbox(label="Enter English text here") | |
| #out_text_chinese = gr.Textbox(label="Your Chinese language output") | |
| b1 = gr.Button("Generate SD") | |
| out_sd = gr.Image(type="pil", label="SD output for the given prompt") | |
| b1.click(get_sd, in_text_prompt, out_sd) #out_gallery ) | |
| demo.launch(enable_queue=True, debug=True) |