20 lines
610 B
Python
20 lines
610 B
Python
import torch
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import clip
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from PIL import Image
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model, preprocess = clip.load("ViT-B/32", device=device)
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image = preprocess(Image.open("CLIP.png")).unsqueeze(0).to(device)
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text = clip.tokenize(["a diagram", "a dog", "a cat"]).to(device)
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with torch.no_grad():
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image_features = model.encode_image(image)
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text_features = model.encode_text(text)
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logits_per_image, logits_per_text = model(image, text)
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probs = logits_per_image.softmax(dim=-1).cpu().numpy()
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print("Label probs:", probs) # prints: [[0.9927937 0.00421068 0.00299572]]
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