Create app.py

app.py

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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()