salomonsky commited on
Commit
165b2f6
1 Parent(s): 79f1585

Update app.py

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Files changed (1) hide show
  1. app.py +1 -15
app.py CHANGED
@@ -12,8 +12,6 @@ from gradio_client import Client, handle_file
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  from huggingface_hub import login
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  from gradio_imageslider import ImageSlider
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-
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- # Configuración inicial
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  translator = Translator()
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  HF_TOKEN = os.environ.get("HF_TOKEN")
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  basemodel = "black-forest-labs/FLUX.1-schnell"
@@ -21,12 +19,9 @@ MAX_SEED = np.iinfo(np.int32).max
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  CSS = "footer { visibility: hidden; }"
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  JS = "function () { gradioURL = window.location.href; if (!gradioURL.endsWith('?__theme=dark')) { window.location.replace(gradioURL + '?__theme=dark'); } }"
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- # Función para habilitar LoRA
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  def enable_lora(lora_add):
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  return basemodel if not lora_add else lora_add
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-
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- # Función asíncrona para generar imágenes
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  async def generate_image(prompt, model, lora_word, width, height, scales, steps, seed):
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  try:
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  if seed == -1:
@@ -39,8 +34,6 @@ async def generate_image(prompt, model, lora_word, width, height, scales, steps,
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  except Exception as e:
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  raise gr.Error(f"Error en {e}")
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-
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- # Función asíncrona para generar imágenes y aplicar upscale
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  async def gen(prompt, lora_add, lora_word, width, height, scales, steps, seed, upscale_factor, process_upscale):
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  model = enable_lora(lora_add)
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  image, seed = await generate_image(prompt, model, lora_word, width, height, scales, steps, seed)
@@ -54,15 +47,11 @@ async def gen(prompt, lora_add, lora_word, width, height, scales, steps, seed, u
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  return [image_path, upscale_image]
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-
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- # Función para aplicar upscale con Finegrain
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  def get_upscale_finegrain(prompt, img_path, upscale_factor):
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  client = Client("finegrain/finegrain-image-enhancer")
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  result = client.predict(input_image=handle_file(img_path), prompt=prompt, negative_prompt="", seed=42, upscale_factor=upscale_factor, controlnet_scale=0.6, controlnet_decay=1, condition_scale=6, tile_width=112, tile_height=144, denoise_strength=0.35, num_inference_steps=18, solver="DDIM", api_name="/process")
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  return result[1]
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-
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- # Configuración de CSS
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  css = """
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  #col-container{
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  margin: 0 auto;
@@ -72,8 +61,7 @@ css = """
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  with gr.Blocks(css=CSS, js=JS, theme="Nymbo/Nymbo_Theme") as demo:
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  with gr.Column(elem_id="col-container"):
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- gr.Markdown("# Flux Upscaled")
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- gr.Markdown("Step 1: Generate image with FLUX schnell; Step 2: UpScale with Finegrain Image-Enhancer")
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  with gr.Group():
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  prompt = gr.Textbox(label="Prompt")
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  with gr.Row():
@@ -100,6 +88,4 @@ with gr.Blocks(css=CSS, js=JS, theme="Nymbo/Nymbo_Theme") as demo:
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  outputs=[output_res]
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  )
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-
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- # Iniciar la aplicación
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  demo.launch()
 
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  from huggingface_hub import login
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  from gradio_imageslider import ImageSlider
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  translator = Translator()
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  HF_TOKEN = os.environ.get("HF_TOKEN")
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  basemodel = "black-forest-labs/FLUX.1-schnell"
 
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  CSS = "footer { visibility: hidden; }"
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  JS = "function () { gradioURL = window.location.href; if (!gradioURL.endsWith('?__theme=dark')) { window.location.replace(gradioURL + '?__theme=dark'); } }"
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  def enable_lora(lora_add):
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  return basemodel if not lora_add else lora_add
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  async def generate_image(prompt, model, lora_word, width, height, scales, steps, seed):
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  try:
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  if seed == -1:
 
34
  except Exception as e:
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  raise gr.Error(f"Error en {e}")
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  async def gen(prompt, lora_add, lora_word, width, height, scales, steps, seed, upscale_factor, process_upscale):
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  model = enable_lora(lora_add)
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  image, seed = await generate_image(prompt, model, lora_word, width, height, scales, steps, seed)
 
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  return [image_path, upscale_image]
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  def get_upscale_finegrain(prompt, img_path, upscale_factor):
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  client = Client("finegrain/finegrain-image-enhancer")
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  result = client.predict(input_image=handle_file(img_path), prompt=prompt, negative_prompt="", seed=42, upscale_factor=upscale_factor, controlnet_scale=0.6, controlnet_decay=1, condition_scale=6, tile_width=112, tile_height=144, denoise_strength=0.35, num_inference_steps=18, solver="DDIM", api_name="/process")
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  return result[1]
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  css = """
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  #col-container{
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  margin: 0 auto;
 
61
 
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  with gr.Blocks(css=CSS, js=JS, theme="Nymbo/Nymbo_Theme") as demo:
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  with gr.Column(elem_id="col-container"):
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+ gr.Markdown("Flux Upscaled +LORA")
 
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  with gr.Group():
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  prompt = gr.Textbox(label="Prompt")
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  with gr.Row():
 
88
  outputs=[output_res]
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  )
90
 
 
 
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  demo.launch()