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Create Simple Image Classification
Browse files- Simple Image Classification +28 -0
Simple Image Classification
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# Import necessary libraries
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from transformers import ViTFeatureExtractor, ViTForImageClassification
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from PIL import Image
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import requests
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import torch
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import matplotlib.pyplot as plt
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# Load pre-trained feature extractor and model
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feature_extractor = ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224')
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model = ViTForImageClassification.from_pretrained('google/vit-base-patch16-224')
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# Load and display the image
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url = "URL_of_the_image"
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image = Image.open(requests.get(url, stream=True).raw)
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plt.imshow(image)
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plt.show()
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# Extract features from the image
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inputs = feature_extractor(images=image, return_tensors="pt")
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# Make predictions
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outputs = model(**inputs)
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logits = outputs.logits
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predicted_class_idx = logits.argmax(-1).item()
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# Get and print the predicted class name
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predicted_class = model.config.id2label[predicted_class_idx]
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print(f'Predicted class: {predicted_class}')
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