added required files

ocr_app.py

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+import streamlit as st
+import cv2
+import numpy as np
+import pytesseract
+from PIL import Image
+import spacy
+
+# Set the Tesseract executable path (update this to your Tesseract installation path)
+pytesseract.pytesseract.tesseract_cmd = r"C:\Users\MAHFOOZ ALAM\anaconda3\Lib\site-packages\pytesseract\pytesseract.py"
+
+# Load the English language model for spaCy
+nlp = spacy.load('en_core_web_sm')
+
+def preprocess_image(image):
+    # Convert to grayscale
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Apply thresholding
+    _, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
+
+    # Noise reduction
+    denoised = cv2.fastNlMeansDenoising(binary)
+
+    # Skew correction
+    coords = np.column_stack(np.where(denoised > 0))
+    angle = cv2.minAreaRect(coords)[-1]
+    if angle < -45:
+        angle = -(90 + angle)
+    else:
+        angle = -angle
+    (h, w) = denoised.shape[:2]
+    center = (w // 2, h // 2)
+    M = cv2.getRotationMatrix2D(center, angle, 1.0)
+    rotated = cv2.warpAffine(denoised, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)
+
+    return rotated
+
+def perform_ocr(image):
+    text = pytesseract.image_to_string(image)
+    return text
+
+def post_process_text(text):
+    doc = nlp(text)
+    processed_text = ' '.join([token.text for token in doc if not token.is_space])
+    return processed_text
+
+def main():
+    st.title("English Handwritten Text OCR App")
+    st.write("Upload an image with handwritten English text for OCR")
+
+    uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+    if uploaded_file is not None:
+        image = Image.open(uploaded_file)
+        st.image(image, caption="Uploaded Image", use_column_width=True)
+
+        if st.button("Perform OCR"):
+            with st.spinner("Processing..."):
+                # Convert PIL Image to numpy array
+                img_array = np.array(image)
+
+                # Preprocess the image
+                processed_img = preprocess_image(img_array)
+
+                # Perform OCR
+                text = perform_ocr(processed_img)
+
+                # Post-process the text
+                processed_text = post_process_text(text)
+
+                st.subheader("OCR Result:")
+                st.write(processed_text)
+
+if __name__ == "__main__":
+    main()