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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) |