Application file

app.py

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+from azure.core.credentials import AzureKeyCredential
+from azure.ai.formrecognizer import FormRecognizerClient, DocumentAnalysisClient
+import pandas as pd
+import numpy as np
+import gradio as gr
+
+
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+model_name = "deepset/bert-base-uncased-squad2"
+
+# a) Get predictions
+nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+
+
+endpoint = "https://invoice-extract.cognitiveservices.azure.com/"
+key = "af03126391e141d482255941fdb16b7c"
+# form_recognizer_client = FormRecognizerClient(endpoint=endpoint, credential=AzureKeyCredential(key))
+document_analysis_client = DocumentAnalysisClient(
+        endpoint=endpoint, credential=AzureKeyCredential(key))
+
+
+def extract_check_info(img):
+    
+    with open(img, "rb") as f:
+        poller = document_analysis_client.begin_analyze_document(
+            "prebuilt-document", document=f)
+        document_data = poller.result()
+    content = document_data.content.strip()
+    QA_input = {
+    'question': 'What is the IFSC code?',
+    'context': content}
+    r1= nlp(QA_input)
+    ifsc_code = r1['answer']
+    
+    QA_input = {
+    'question': 'What is the A/C Number?',
+    'context': content}
+    r2 = nlp(QA_input)
+    ac_number = r2['answer']
+    
+    QA_input = {
+    'question': 'What is the person name?',
+    'context': content}
+    r3 = nlp(QA_input)
+    person_name = r3['answer']
+    
+    return ifsc_code, ac_number, person_name
+
+
+
+
+if __name__ = "__main__":
+    
+    iface = gr.Interface(fn=extract_check_info,
+                    inputs=[gr.inputs.Image(type='filepath', label='Input')],
+                    outputs = [gr.outputs.Textbox(type='text', label='IFSC code'),
+                              gr.outputs.Textbox(type='text', label='Account Number'),
+                              gr.outputs.Textbox(type='text', label='Beneficiary Name')],
+                    title="Check information extraction demo")
+    iface.launch()
+