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import os
#https://huggingface.co/spaces/Galis/room_interior_quality/tree/main
STABILITY_HOST = os.environ["STABILITY_HOST"]
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 ,design,x_prompt,alt_prompt,strength,guidance_scale,steps):
# Read the size of the image
img = Image.open(path)
width, height = img.size
# Calculate the new size of the image, making sure that the width and height are multiples of 64
new_width = ((width + 63) // 64) * 64
new_height = ((height + 63) // 64) * 64
# Resize the image
img = img.resize((new_width, new_height), resample=Image.Resampling.BILINEAR)
max_attempts = 5 # maximum number of attempts before giving up
attempts = 0 # current number of attempts
while attempts < max_attempts:
try:
if x_prompt == True:
prompt = alt_prompt
else:
try:
caption, keywords = generate_caption_keywords(design)
prompt = keywords
except:
prompt = design
# call the GRPC service to generate the image
answers = stability_api.generate(
prompt,
init_image=img,
seed=54321,
start_schedule=strength,
)
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))
img2 = img2.resize((new_width, new_height), resample=Image.Resampling.BILINEAR)
img2.save("new_image.jpg")
print(type(img2))
# if the function reaches this point, it means it succeeded, so we can return the result
return img2
except Exception as e:
# if an exception is thrown, we will increment the attempts counter and try again
attempts += 1
print("Attempt {} failed: {}".format(attempts, e))
# if the function reaches this point, it means the maximum number of attempts has been reached, so we will raise an exception
raise Exception("Maximum number of attempts reached, unable to generate image")
import gradio as gr
gr.Interface(img2img, [gr.Image(source="upload", type="filepath", label="Input Image"),
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 by Cohere command Langauge model",value = 'interior design'),
gr.Checkbox(label="Check Custom design if you already have prompt",value = False),
gr.Textbox(label = ' Input custom Prompt Text'),
gr.Slider(label='Strength , try with multiple value betweens 0.55 to 0.9 ', 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(),
examples =[['1.png','interior design of living room','False','interior design',0.6,7,50],
['2.png','interior design of hall ','False','interior design',0.7,7,50],
['3.png','interior design of bedroom','False','interior design',0.6,7,50]],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 your thoughts. 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)
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