27 lines
825 B
Python
27 lines
825 B
Python
import gradio as gr
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import torch
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from transformers import ViTFeatureExtractor, ViTForImageClassification
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model = ViTForImageClassification.from_pretrained('nateraw/vit-age-classifier')
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transforms = ViTFeatureExtractor.from_pretrained('nateraw/vit-age-classifier')
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def image_classification(image):
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inputs = transforms(image, return_tensors='pt')
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logits = model(**inputs).logits
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predicted_label = logits.argmax(-1).item()
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return model.config.id2label[predicted_label]
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demo = gr.Interface(fn=image_classification,
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inputs=gr.Image(),
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outputs='text',
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title = "年龄划分",
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examples = ['dog.jpeg'])
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if __name__ == "__main__":
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demo.queue(concurrency_count=3)
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demo.launch(server_name = "0.0.0.0", server_port = 7027)
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