import os os.environ['STABILITY_HOST'] = 'grpc.stability.ai:443' STABILITY_KEY = os.environ["STABILITY_KEY"] cohere_key = os.environ["cohere_key"] import cohere 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 = True), 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 ﺑَﻴﺖ 🏡💡🤖, Transform your space with the power of artificial intelligence. '+ "", description="Baith AI ﺑَﻴﺖ 🏡💡🤖 is an 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 or reaserch this space konnect me @[here](https://www.linkedin.com/in/sallu-mandya/)").launch(share = True, debug = True)