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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.Blocks.load(name="spaces/stabilityai/stable-diffusion", 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), 7.5,float(1024), 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) |