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import gradio as gr
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from transformers import BlipProcessor, BlipForConditionalGeneration
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from PIL import Image
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processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
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def generate_caption(image):
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inputs = processor(image, return_tensors="pt")
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outputs = model.generate(**inputs)
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description = processor.decode(outputs[0], skip_special_tokens=True)
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return description
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gradio_app = gr.Interface(
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fn=generate_caption,
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inputs=gr.Image(type="pil"),
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outputs="text",
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title="图片描述生成器",
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description="上传一张图片，生成相应的描述。"
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)
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if __name__ == "__main__":
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gradio_app.launch()
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