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import gradio as gr | |
from transformers import pipeline | |
# 创建用于图像到文本的 pipeline | |
ocr_pipe = pipeline("image-to-text", model="microsoft/trocr-base-handwritten") | |
# 创建用于语法纠正的 pipeline | |
grammar_correction_pipe = pipeline("text2text-generation", model="flexudy/t5-base-multi-sentence-doctor") | |
def process_image_and_correct_grammar(input_image): | |
# 使用 OCR 模型识别图像中的文本 | |
ocr_results = ocr_pipe(input_image) | |
recognized_text = ocr_results[0]['generated_text'] | |
# 使用语法纠正模型纠正文本 | |
corrected_text_results = grammar_correction_pipe(recognized_text) | |
corrected_text = corrected_text_results[0]['generated_text'] | |
# 返回原始文本和纠正后的文本 | |
return {"Original Text": recognized_text, "Corrected Text": corrected_text} | |
# 创建 Gradio 接口 | |
iface = gr.Interface( | |
fn=process_image_and_correct_grammar, # 指定处理函数 | |
inputs=gr.inputs.Image(type='pil', label="Upload your image here or use your camera"), # 设置输入为图片 | |
outputs=[gr.outputs.Textbox(label="Original Text"), gr.outputs.Textbox(label="Corrected Text")], # 设置输出为两个文本框 | |
title="OCR and Grammar Correction", # 接口标题 | |
description="Upload an image and the text in the image will be recognized and grammatically corrected." # 接口描述 | |
) | |
# 启动 Gradio 应用 | |
iface.launch() | |