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| import requests | |
| import shutil | |
| from PIL import Image | |
| from io import BytesIO | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import pandas as pd | |
| import random | |
| import gradio as gr | |
| design='india' | |
| def lexica(design,n): | |
| request=requests.get(f'https://lexica.art/api/v1/search?q={design}') | |
| request.json() | |
| data = request.json() | |
| data_items = list(data.items()) | |
| random.shuffle(data_items) | |
| data = dict(data_items) | |
| image_urls = [] | |
| image_prompts = [] | |
| image_gallery=[] | |
| for key, value in data.items(): | |
| for i in range(n): | |
| image_url = value[i]['src'] | |
| if isinstance(image_url, list): | |
| image_url = image_url[0] | |
| image_urls.append(image_url) | |
| image_prompts.append(value[i]['prompt']) | |
| image_gallery.append(value[i]['gallery']) | |
| images = [] | |
| # Loop through the image URLs | |
| for url in image_urls: | |
| # Download the image from the URL | |
| response = requests.get(url) | |
| # Load the image data into PIL format | |
| image = Image.open(BytesIO(response.content)) | |
| # Add the image to the list | |
| images.append(image) | |
| # df = pd.DataFrame(image_prompts, columns=["Lexica Prompt"], index=range(1, len(image_prompts)+1)) | |
| # df.index.name = "Sr. No." | |
| df = pd.DataFrame({ 'image_gallery': image_gallery,'image_prompts': image_prompts}) | |
| def make_clickable(val): | |
| return '<a href="{}">{}</a>'.format(val, val) | |
| # df.style.format({'image_gallery': make_clickable}) | |
| df.style.format({'image_prompts': make_clickable}).set_properties(subset=['image_prompts'], width=30) | |
| for image in images: | |
| array = np.array(image) | |
| return images , df | |
| design='india' | |
| # lexica(design) | |
| inputs =[ gr.Textbox(label = 'Enter prompt to search Lexica.art'), | |
| gr.Slider(label='Number of images ', minimum = 4, maximum = 20, step = 1, value = 4)] | |
| outputs= [gr.Gallery(lable='Output gallery').style(grid=4,height=100,container=True), | |
| gr.Dataframe(label='links and prompts for corresponding images')] | |
| # Create and launch the interface | |
| interface = gr.Interface(lexica, | |
| inputs=inputs, | |
| outputs=outputs, | |
| examples =[ ['trending digital art', 5], | |
| ['beautiful home', 5], | |
| ['interior design of living room', 5]] | |
| , | |
| title = "" +' 🔍 🖌️🎨 Lexica Art - A Search Engine for Generative Art Prompts and Works '+ "", | |
| description="🔍🖌️ 🎨 lexica huggingface space , Find inspiration and discover new generative artworks with Lexica Art, a search engine built by by @[Sharif shameem](https://twitter.com/sharifshameem) . Explore a vast collection of prompts and corresponding artworks, and let your imagination take over as you create your own masterpieces. \n\n Visit @[baith_al_suroor](https://huggingface.co/spaces/Xhaheen/Baith-al-suroor) to redesign your home interiors for FREE \n\n💡🖌️ spaces built with ❤️ @[Xhaheen](https://www.linkedin.com/in/sallu-mandya)") | |
| interface.launch(debug=True) |