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Update app.py
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app.py
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#Acknowledgments:
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#This project is inspired by:
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#1. https://github.com/haltakov/natural-language-image-search by Vladimir Haltakov
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#2. OpenAI's CLIP
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#Importing all the necessary libraries
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import torch
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import requests
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from transformers import CLIPProcessor, CLIPModel, CLIPTokenizer, CLIPConfig
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from sentence_transformers import SentenceTransformer, util
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Define model
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photo_ids = list(photo_ids['photo_id'])
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def encode_text(text):
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with torch.no_grad():
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# Encode and normalize the description using CLIP
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text_encoded = model.get_text_features(**inputs).detach().numpy()
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return text_encoded
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def encode_image(image):
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image = PILIMAGE.fromarray(image.astype('uint8'), 'RGB')
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with torch.no_grad():
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#Importing all the necessary libraries
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import torch
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import requests
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from transformers import CLIPProcessor, CLIPModel, CLIPTokenizer, CLIPConfig
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from sentence_transformers import SentenceTransformer, util
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Define model
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photo_ids = list(photo_ids['photo_id'])
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def encode_text(text):
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with torch.no_grad():
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# Encode and normalize the description using CLIP
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text_encoded = model.get_text_features(**inputs).detach().numpy()
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return text_encoded
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def encode_image(image):
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image = PILIMAGE.fromarray(image.astype('uint8'), 'RGB')
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with torch.no_grad():
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