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app.py

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+import pandas as pd
+import gradio as gr
+import torch
+import easyocr
+from docx import Document
+
+torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/english.png', 'english.png')
+
+def inference(img):
+    # Here, you can add your image processing logic using EasyOCR
+    # For demonstration purposes, let's extract text from the input image and save it in a Word document
+    # Perform OCR on the input image
+    reader = easyocr.Reader(["en"])
+    bounds = reader.readtext(img)
+    # im = PIL.Image.open(img.name)
+    # draw_boxes(im, bounds)
+    # im.save('result.jpg')
+
+
+    # Download the input image
+    # response = requests.get(img, stream=True)
+    # response.raise_for_status()
+
+
+    # reader = easyocr.Reader(['en'])
+    result = pd.DataFrame(bounds).iloc[: , 1:]
+    
+
+    # Save the extracted text to a Word document
+    output_file_path = "output_document.docx"
+    document = Document()
+    for text in result[1]:
+        document.add_paragraph(text)
+        # print(text)
+    document.save(output_file_path)
+    df = result.rename(index = {"1": "Text","2":"Confidence"},inplace = True) 
+    # print(df.columns.values[0])
+    #pd.DataFrame(result , columns=["Text", "Confidence"])
+    return  output_file_path , pd.DataFrame(bounds).iloc[: , 1:]#.rename(index = {1: "Text",2:"Confidence"},inplace = True) 
+    # return pd.DataFrame(bounds).iloc[: , 1:]
+
+title = 'EasyOCR'
+description = 'Gradio demo for EasyOCR. EasyOCR demo supports 80+ languages.To use it, simply upload your image and choose a language from the dropdown menu, or click one of the examples to load them. Read more at the links below.'
+article = "<p style='text-align: center'><a href='https://www.jaided.ai/easyocr/'>Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.</a> | <a href='https://github.com/JaidedAI/EasyOCR'>Github Repo</a></p>"
+examples = [['english.png',['en']],['report.jpeg',['en']]]
+css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
+choices = [
+  
+    "en",
+    "ms",
+
+]
+gr.Interface(
+    fn=inference,
+    # inputs="image", outputs="text",
+    inputs=[gr.Image( label='Input')],
+    outputs=[ gr.File(label="Output Word Document"),gr.Dataframe(label='Result', type="pandas",headers=['Text', 'Confidence'], wrap=True)],
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+    css=css
+    ).launch(debug=True)
+
+# gr.Interface(fn=predict, inputs="image", outputs="text")