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import requests |
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import shutil |
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from PIL import Image |
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from io import BytesIO |
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import numpy as np |
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import matplotlib.pyplot as plt |
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import pandas as pd |
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import random |
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import gradio as gr |
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design='india' |
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def lexica(design,n): |
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request=requests.get(f'https://lexica.art/api/v1/search?q={design}') |
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request.json() |
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data = request.json() |
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data_items = list(data.items()) |
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random.shuffle(data_items) |
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data = dict(data_items) |
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image_urls = [] |
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image_prompts = [] |
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for key, value in data.items(): |
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for i in range(n): |
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image_url = value[i]['src'] |
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if isinstance(image_url, list): |
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image_url = image_url[0] |
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image_urls.append(image_url) |
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image_prompts.append(value[i]['prompt']) |
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images = [] |
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for url in image_urls: |
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response = requests.get(url) |
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image = Image.open(BytesIO(response.content)) |
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images.append(image) |
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df = pd.DataFrame(image_prompts, columns=["Lexica Prompt"], index=range(1, len(image_prompts)+1)) |
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df.index.name = "Sr. No." |
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for image in images: |
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array = np.array(image) |
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return images , df |
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design='india' |
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inputs =[ gr.Textbox(label = 'Enter prompt to search'), |
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gr.Slider(label='Number of images ', minimum = 4, maximum = 20, step = 1, value = 4)] |
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outputs= [gr.Gallery(lable='Output gallery').style(grid=1), |
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gr.Dataframe(label='prompts for corresponding images')] |
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interface = gr.Interface(lexica, |
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inputs=inputs, |
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outputs=outputs, |
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examples =[ ['trending digital art', 5], |
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['beautiful home', 5], |
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['interior design of living room', 5]] |
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, |
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title = "" +' A Search Engine for Generative Art Prompts and Works '+ "", |
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description=" Find more powerful tools at [AI Beast](https://aibeast.net) and follow for updates . [Follow](https://www.facebook.com/abbas143office) ❤️") |
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interface.launch(debug=True) |