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| import os | |
| from PIL import ImageDraw | |
| from PIL import ImageFont | |
| #https://huggingface.co/spaces/Galis/room_interior_quality/tree/main/FGoWx7peJuJ/secret_santa | |
| 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 | |
| import math | |
| from math import sqrt | |
| 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 ,secret_key,design,x_prompt,alt_prompt,strength,guidance_scale,steps): | |
| # Read the size of the image | |
| ############################ | |
| img = Image.open(path) | |
| width, height = img.size | |
| num_pixels = width * height | |
| # Calculate the maximum number of pixels allowed | |
| max_pixels = 1048576 | |
| # Calculate the new size of the image, making sure that the number of pixels does not exceed the maximum limit | |
| if width * height > max_pixels: | |
| # Calculate the new width and height of the image | |
| ratio = width / height | |
| new_width = int(math.sqrt(max_pixels * ratio)) | |
| new_height = int(math.sqrt(max_pixels / ratio)) | |
| else: | |
| new_width = width | |
| new_height = height | |
| # Make sure that either the width or the height of the resized image is a multiple of 64 | |
| if new_width % 64 != 0: | |
| new_width = ((new_width + 63) // 64) * 64 | |
| if new_height % 64 != 0: | |
| new_height = ((new_height + 63) // 64) * 64 | |
| # Resize the image | |
| img = img.resize((new_width, new_height), resample=Image.BILINEAR) | |
| # Check if the number of pixels in the resized image is within the maximum limit | |
| # If not, adjust the width and height of the image to bring the number of pixels within the maximum limit | |
| if new_width * new_height > max_pixels: | |
| while new_width * new_height > max_pixels: | |
| new_width -= 1 | |
| new_height = int(max_pixels / new_width) | |
| # Calculate the closest multiple of 64 for each value | |
| if new_width % 64 != 0: | |
| new_width = (new_width // 64) * 64 | |
| if new_height % 64 != 0: | |
| new_height = (new_height // 64) * 64 | |
| # Make sure that the final values are less than the original values | |
| if new_width > 1407: | |
| new_width -= 64 | |
| if new_height > 745: | |
| new_height -= 64 | |
| new_height ,new_width | |
| # Initialize the values | |
| widthz = new_width | |
| heightz = new_height | |
| # Calculate the closest multiple of 64 for each value | |
| if widthz % 64 != 0: | |
| widthz = (widthz // 64) * 64 | |
| if heightz % 64 != 0: | |
| heightz = (heightz // 64) * 64 | |
| # Make sure that the final values are less than the original values | |
| if widthz > 1407: | |
| widthz -= 64 | |
| if heightz > 745: | |
| heightz -= 64 | |
| img = img.resize((widthz, heightz), resample=Image.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.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 | |
| if secret_key not in os.environ['secretz']: | |
| draw = ImageDraw.Draw(img2) | |
| # Set the font and text color | |
| font = ImageFont.truetype('arial.ttf', 32) | |
| text_color = (255, 255, 255) | |
| # Get the size of the image | |
| width, height = img2.size | |
| # Calculate the x and y coordinates for the text | |
| text_x = 10 | |
| text_y = height - 100 | |
| # Draw the text on the image | |
| draw.text((text_x, text_y), 'Please enter secret key to get HD image without \n watermark', font=font, fill=text_color) | |
| # Draw the diagonal lines | |
| line_color = (0, 0, 0) | |
| draw.line((0, 0) + (width, height), fill=line_color, width=5) | |
| draw.line((0, height) + (width, 0), fill=line_color, width=5) | |
| # Save the image with the watermark | |
| img2.save('image_with_watermark.jpg') | |
| img2 | |
| 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.Textbox(label = 'enter secret key to get HD image without watermark , connect with Xhaheen to get key',value = 'secret_santa', type="password" ), | |
| 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 GPT-3/Cohere Language 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',"xxx",'interior design of living room','False','interior design',0.6,7,50], | |
| ['2.png',"xxx",'interior design of hall ','False','interior design',0.7,7,50], | |
| ['3.png',"xxx",'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 deeptech app that uses the power of artificial intelligence to transform your space. With the Cohere/GPT3 language 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 / get secret key for research purpose on this space konnect me @[Xhaheen](https://www.linkedin.com/in/sallu-mandya/)").launch( show_api=False,debug = True) | |