Update app.py

app.py

@@ -17,19 +17,18 @@ from datasets import load_dataset, Image
 from PIL import Image
 from paddleocr import PaddleOCR
 from save_data import flag
-            
+from transformers import pipeline  # Importing the pipeline
+
 """
 Paddle OCR
 """
 def ocr_with_paddle(img):
     finaltext = ''
     ocr = PaddleOCR(lang='en', use_angle_cls=True)
-    # img_path = 'exp.jpeg'
     result = ocr.ocr(img)
-    
     for i in range(len(result[0])):
         text = result[0][i][1][0]
-        finaltext += ' '+ text
+        finaltext += ' ' + text
     return finaltext
 
 """
@@ -37,84 +36,88 @@ Keras OCR
 """
 def ocr_with_keras(img):
     output_text = ''
-    pipeline=keras_ocr.pipeline.Pipeline()
-    images=[keras_ocr.tools.read(img)]
-    predictions=pipeline.recognize(images)
-    first=predictions[0]
-    for text,box in first:
-        output_text += ' '+ text
+    pipeline = keras_ocr.pipeline.Pipeline()
+    images = [keras_ocr.tools.read(img)]
+    predictions = pipeline.recognize(images)
+    first = predictions[0]
+    for text, box in first:
+        output_text += ' ' + text
     return output_text
 
 """
 easy OCR
 """
-# gray scale image
+# grayscale image
 def get_grayscale(image):
     return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
 
 # Thresholding or Binarization
 def thresholding(src):
-    return cv2.threshold(src,127,255, cv2.THRESH_TOZERO)[1]
+    return cv2.threshold(src, 127, 255, cv2.THRESH_TOZERO)[1]
+
 def ocr_with_easy(img):
-    gray_scale_image=get_grayscale(img)
+    gray_scale_image = get_grayscale(img)
     thresholding(gray_scale_image)
-    cv2.imwrite('image.png',gray_scale_image)
-    reader = easyocr.Reader(['th','en'])
-    bounds = reader.readtext('image.png',paragraph="False",detail = 0)
+    cv2.imwrite('image.png', gray_scale_image)
+    reader = easyocr.Reader(['th', 'en'])
+    bounds = reader.readtext('image.png', paragraph="False", detail=0)
     bounds = ''.join(bounds)
     return bounds
-        
+
 """
 Generate OCR
 """
-def generate_ocr(Method,img):
-    
+def generate_ocr(Method, img):
     text_output = ''
     if (img).any():
-        add_csv = []
-        image_id = 1
-        print("Method___________________",Method)
+        print("Method___________________", Method)
         if Method == 'EasyOCR':
             text_output = ocr_with_easy(img)
         if Method == 'KerasOCR':
             text_output = ocr_with_keras(img)
         if Method == 'PaddleOCR':
             text_output = ocr_with_paddle(img)
-       
+        
         try:
-            flag(Method,text_output,img)
+            flag(Method, text_output, img)
         except Exception as e:
             print(e)
-        return text_output
+        
+        # Generate Text using FLAN-T5 model
+        text_gen = generate_text_with_flan_t5(text_output)
+        return text_gen
     else:
         raise gr.Error("Please upload an image!!!!")
-    
-    # except Exception as e:
-    #     print("Error in ocr generation ==>",e)
-    #     text_output = "Something went wrong"
-    # return text_output
-    
+
+"""
+Text Generation using FLAN-T5
+"""
+def generate_text_with_flan_t5(input_text):
+    # Load the pre-trained FLAN-T5 model
+    pipe = pipeline("text2text-generation", model="google/flan-t5-large")
+
+    # Use the model to generate a response based on the OCR output
+    output = pipe(input_text)
+    return output[0]['generated_text']
+
 
 """
 Create user interface for OCR demo
 """
 
-# image = gr.Image(shape=(300, 300))
 image = gr.Image()
-method = gr.Radio(["PaddleOCR","EasyOCR", "KerasOCR"],value="PaddleOCR")
-output = gr.Textbox(label="Output")
+method = gr.Radio(["PaddleOCR", "EasyOCR", "KerasOCR"], value="PaddleOCR")
+output = gr.Textbox(label="Generated Text")
 
 demo = gr.Interface(
     generate_ocr,
-    [method,image],
+    [method, image],
     output,
-    title="Optical Character Recognition",
+    title="Optical Character Recognition and Text Generation",
     css=".gradio-container {background-color: lightgray} #radio_div {background-color: #FFD8B4; font-size: 40px;}",
-    article = """<p style='text-align: center;'>Feel free to give us your thoughts on this demo and please contact us at 
+    article="""<p style='text-align: center;'>Feel free to give us your thoughts on this demo and please contact us at 
                     <a href="mailto:[email protected]" target="_blank">[email protected]</a> 
                     <p style='text-align: center;'>Developed by: <a href="https://www.pragnakalp.com" target="_blank">Pragnakalp Techlabs</a></p>"""
-    
-
 )
-# demo.launch(enable_queue = False)
-demo.launch()
+
+demo.launch()