app.py

import streamlit as st
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
from PIL import Image
import requests

# 加载模型和处理器
processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten")

def load_image(image_file):
    img = Image.open(image_file)
    return img

def predict(image):
    # 处理图片
    pixel_values = processor(images=image, return_tensors="pt").pixel_values
    # 生成预测
    output_ids = model.generate(pixel_values)
    # 转换输出文本
    output_text = processor.decode(output_ids[0], skip_special_tokens=True)
    return output_text

def main():
    st.title("图片物体识别")
    image_file = st.file_uploader("上传一张图片", type=["jpg", "png", "jpeg"])

    if image_file is not None:
        # 显示图片
        image = load_image(image_file)
        st.image(image, caption='上传的图片', use_column_width=True)
        # 预测图片
        if st.button("识别图片"):
            result_text = predict(image)
            st.write(f"识别结果: {result_text}")

if __name__ == '__main__':
    main()