Update app.py

app.py

@@ -1,14 +1,10 @@
-import os 
-os.system('pip install -r requirements.txt')
-
 import streamlit as st
 from PIL import Image
 import numpy as np
 from streamlit_cropper import st_cropper
-from tesserocr import PyTessBaseAPI
 from annotated_text import annotated_text
 from simpletransformers.ner import NERModel
-
+import pytesseract
 # Function to resize the image based on desired DPI
 def resize_image(image, desired_dpi):
     # Calculate the current DPI
@@ -25,15 +21,7 @@ def resize_image(image, desired_dpi):
 
 # Function to perform OCR on the image
 def perform_ocr(image):
-    
-    with PyTessBaseAPI(path=r'model', lang="tha") as api:
-        api.SetVariable('preserve_interword_spaces', '1')
-        
-        im_gray = image.convert("L")
-        cropped_img_bytes = im_gray.tobytes()  # Convert grayscale image to bytes
-        api.SetImage(Image.frombytes('L', im_gray.size, cropped_img_bytes))  # Set the image from bytes
-
-        extracted_text = api.GetUTF8Text()
+    extracted_text =pytesseract.image_to_string(image=image, lang='tha')
 
     return extracted_text
 
@@ -96,16 +84,16 @@ def main():
 
             desired_dpi = 300
 
-            # Resize the image
+            # # Resize the image
             resized_image = resize_image(cropped_img, desired_dpi)
 
-            # Display the image
+            # # Display the image
             st.image(resized_image)
             # Perform OCR
-            extracted_text = perform_ocr(resized_image)
+            # extracted_text = 
 
             # Display extracted text
-            txt_input = st.text_area("โปรดตรวจสอบความถูกต้อง", extracted_text)
+            txt_input = st.text_area("โปรดตรวจสอบความถูกต้อง", perform_ocr(cropped_img))
 
             word_output = ""
             word_tuple = ()
@@ -156,15 +144,15 @@ if __name__ == '__main__':
         Hardware_Type = False
     # Model initialization
     _NER_TAGS = ['0', '1']
-    try:
-        model = NERModel(
-            model_name=r"model",
-            model_type="camembert",
-            labels=_NER_TAGS,
-            use_cuda=Hardware_Type
-        )
-        main()
-    except:
-        st.warning("Cuda not available, Please checking your hardware")
+    # try:
+    model = NERModel(
+        model_name=r"model",
+        model_type="camembert",
+        labels=_NER_TAGS,
+        use_cuda=Hardware_Type
+    )
+    main()
+    # except:
+    #     st.warning("Cuda not available, Please checking your hardware")
     aib_logo = Image.open(r'aib_logo.png')
     add_logo = st.sidebar.image(aib_logo)