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Baith-al-suroor
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import os
os.environ['STABILITY_HOST'] = 'grpc.stability.ai:443'
STABILITY_KEY = os.environ["STABILITY_KEY"]
cohere_key = os.environ["cohere_key"]
import cohere
import random
co = cohere.Client(cohere_key)
import io
import os
import warnings

from IPython.display import display
from PIL import Image
from stability_sdk import client
import stability_sdk.interfaces.gooseai.generation.generation_pb2 as generation
from PIL import Image

stability_api = client.StabilityInference(
    key=os.environ['STABILITY_KEY'], 
    verbose=True,
)


def generate_caption_keywords(prompt, model='command-xlarge-20221108', max_tokens=200, temperature=random.uniform(0.1, 2), k=0, p=0.75, frequency_penalty=0, presence_penalty=0, stop_sequences=[]):
    
    response = co.generate(
      model=model,
      prompt=prompt,
      max_tokens=max_tokens,
      temperature=temperature,
      k=k,
      p=p,
      frequency_penalty=frequency_penalty,
      presence_penalty=presence_penalty,
      stop_sequences=stop_sequences,
      return_likelihoods='NONE')

    def highlight_keywords(text):
        keywords = []
        text = text.lower()
        text = re.sub(r'[^a-z\s]', '', text) # remove punctuation
        text = re.sub(r'\b(the|and|of)\b', '', text) # remove stop words
        words = text.split()
        for word in words:
            if word not in keywords:
                keywords.append(word)
        return keywords

    caption = response.generations[0].text
    keywords = highlight_keywords(caption)
    keywords_string = ', '.join(keywords)

    return caption, keywords_string


def img2img( path ,is_HD,design,x_prompt,alt_prompt,strength,guidance_scale,steps):



  img = Image.open(path)

  try:
        caption, keywords = generate_caption_keywords(design)
        prompt = keywords
  except:
    
    prompt = design
    
 

  if x_prompt == True:

    prompt=alt_prompt


  answers = stability_api.generate(
      
      prompt,
      
      init_image=img,
      seed=54321, # if we're passing in an image generated by SD, you may get better results by providing a different seed value than was used to generate the image
      start_schedule=strength, # this controls the "strength" of the prompt relative to the init image
  )
  
  # iterating over the generator produces the api response
  for resp in answers:
      for artifact in resp.artifacts:
          if artifact.finish_reason == generation.FILTER:
              warnings.warn(
                  "Your request activated the API's safety filters and could not be processed."
                  "Please modify the prompt and try again.")
          if artifact.type == generation.ARTIFACT_IMAGE:
              img2 = Image.open(io.BytesIO(artifact.binary))
              im1 = img2.save("new_image.jpg")
 
              print(type(img2))
  return img2



import gradio as gr  

gr.Interface(img2img,  [gr.Image(source="upload", type="filepath", label="Input Image"),
                        gr.Checkbox(label="Click HD to get HD output(Not working in HF spaces ,contact for Colab)",value = False),
                        gr.Dropdown(['interior design of living room', 
                                         'interior design of gaming room',
                                         'interior design of kitchen',
                                         'interior design of bedroom',
                                         'interior design of bathroom',
                                         'interior design of office',
                                         'interior design of meeting room',
                                         'interior design of personal room'],label="Click here to select your design",value = 'interior design'), 
                        gr.Checkbox(label="Custom design",value = False),

                        gr.Textbox(label = ' Input custom Prompt Text'),
                        gr.Slider(label='Strength', minimum = 0, maximum = 1, step = .01, value = .65),
                        gr.Slider(2, 15, value = 7, label = 'Guidence Scale'),
                        gr.Slider(10, 50, value = 50, step = 1, label = 'Number of Iterations')
                        ], 
                        gr.Image(), title = "" +'Baith-al-suroor بَیتُ الْسرور  🏡💡🤖, Transform your space with the power of artificial intelligence. '+ "",
                                    description="Baith al suroor بَیتُ الْسرور  (house of happiness in Arabic)  🏡💡🤖  is a simple app that uses the power of artificial intelligence to transform your space. With the Cohere language Command model, it can generate descriptions of your desired design, and the Stable Diffusion algorithm creates relevant images to bring your vision to life. Give Baith AI a try and see how it can elevate your interior design.--if you want to scale / reaserch / build mobile app on this space konnect me   @[here](https://www.linkedin.com/in/sallu-mandya/)").launch( debug = True)