gojiteji commited on
Commit
6438cbe
1 Parent(s): 243f370

Update app.py

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Files changed (1) hide show
  1. app.py +3 -5
app.py CHANGED
@@ -54,7 +54,6 @@ def sd2_inference(pipeline, prompts, params, seed = 42, num_inference_steps = 50
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  HF_ACCESS_TOKEN = os.environ["HFAUTH"]
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  # Load Model
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- # - Reference: https://github.com/huggingface/diffusers/blob/main/README.md
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  pipeline, params = FlaxStableDiffusionPipeline.from_pretrained(
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  "CompVis/stable-diffusion-v1-4",
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  use_auth_token = HF_ACCESS_TOKEN,
@@ -73,7 +72,6 @@ model = FlaxVisionEncoderDecoderModel.from_pretrained(loc)
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  gen_kwargs = {"max_length": 16, "num_beams": 4}
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- # This takes sometime when compiling the first time, but the subsequent inference will be much faster
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  def generate(pixel_values):
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  output_ids = model.generate(pixel_values, **gen_kwargs).sequences
@@ -95,11 +93,11 @@ def image2text(image):
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  def text_to_image_and_image_to_text(text=None,image=None):
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- txt=None
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  img=None
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  if image != None:
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  txt=image2text(image)
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- if text !=None:
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  images = sd2_inference(pipeline, [text], params, seed = 42, num_inference_steps = 5 )
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  img = images[0]
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  return img,txt
@@ -107,7 +105,7 @@ def text_to_image_and_image_to_text(text=None,image=None):
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  if __name__ == '__main__':
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  interFace = gr.Interface(fn=text_to_image_and_image_to_text,
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- inputs=[gr.inputs.Textbox(placeholder="Enter the text to Encode to an image",value=None, label="Text to Encode to Image ",lines=1,optional=True),gr.Image(type="pil",value=None,label="Image to Decode to text",optional=True)],
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  outputs=[gr.outputs.Image(type="pil", label="Encoded Image"),gr.outputs.Textbox( label="Decoded Text")],
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  title="T2I2T: Text2Image2Text imformation transmiter",
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  description="⭐️The next generation of QR codes, an information sharing tool via images⭐️ Error rates are high & Image generation takes about 200 seconds.",
 
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  HF_ACCESS_TOKEN = os.environ["HFAUTH"]
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  # Load Model
 
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  pipeline, params = FlaxStableDiffusionPipeline.from_pretrained(
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  "CompVis/stable-diffusion-v1-4",
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  use_auth_token = HF_ACCESS_TOKEN,
 
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  gen_kwargs = {"max_length": 16, "num_beams": 4}
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  def generate(pixel_values):
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  output_ids = model.generate(pixel_values, **gen_kwargs).sequences
 
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  def text_to_image_and_image_to_text(text=None,image=None):
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+ txt=""
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  img=None
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  if image != None:
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  txt=image2text(image)
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+ if text !="":
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  images = sd2_inference(pipeline, [text], params, seed = 42, num_inference_steps = 5 )
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  img = images[0]
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  return img,txt
 
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  if __name__ == '__main__':
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  interFace = gr.Interface(fn=text_to_image_and_image_to_text,
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+ inputs=[gr.inputs.Textbox(placeholder="Enter the text to Encode to an image", label="Text to Encode to Image ",lines=1,optional=True),gr.Image(type="pil",label="Image to Decode to text",optional=True)],
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  outputs=[gr.outputs.Image(type="pil", label="Encoded Image"),gr.outputs.Textbox( label="Decoded Text")],
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  title="T2I2T: Text2Image2Text imformation transmiter",
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  description="⭐️The next generation of QR codes, an information sharing tool via images⭐️ Error rates are high & Image generation takes about 200 seconds.",