25 lines
974 B
Python
25 lines
974 B
Python
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#图像分类
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import gradio as gr
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from transformers import ViTFeatureExtractor, ViTForImageClassification
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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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def image_classification(image):
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inputs = feature_extractor(images=image, return_tensors="pt")
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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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return model.config.id2label[predicted_class_idx]
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demo = gr.Interface(fn=image_classification,
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inputs=gr.Image(),
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outputs=gr.Label(num_top_classes=1),
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title = "图像分类",
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allow_flagging="never",
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examples = ['cat.jpeg', 'dog.jpeg', 'zebra.jpeg'])
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if __name__ == "__main__":
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demo.queue(concurrency_count=3).launch(server_name = "0.0.0.0", server_port = 7000, max_threads=40)
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