Merge pull request #179 from litesh1123/smart_select_gui

Smart select feature gui created

Author: sanjay-kv

Smart_select features/smart_select_gui.py

@@ -0,0 +1,144 @@
+import os
+import cv2
+import pytesseract
+import numpy as np
+from tkinter import Tk, filedialog, Text, Button, Label, Scrollbar, RIGHT, Y, BOTH, END, Frame, Entry, messagebox
+from PIL import Image, ImageEnhance, ImageFilter, ImageTk
+
+# Manually specify the path to the Tesseract executable
+pytesseract.pytesseract.tesseract_cmd = r'C:\Users\kulitesh\Tesseract-OCR\Tesseract-OCR\tesseract.exe'
+
+def preprocess_image(image_path):
+    # Open the image using PIL
+    image = Image.open(image_path)
+
+    # Convert to grayscale
+    image = image.convert('L')
+
+    # Increase contrast
+    enhancer = ImageEnhance.Contrast(image)
+    image = enhancer.enhance(2)
+
+    # Apply a median filter to remove noise
+    image = image.filter(ImageFilter.MedianFilter(size=3))
+
+    # Convert the image to a NumPy array for OpenCV processing
+    image = cv2.cvtColor(np.array(image), cv2.COLOR_GRAY2BGR)
+
+    return image
+
+def segment_image(image):
+    # Convert to grayscale
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Apply adaptive thresholding
+    binary = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
+
+    # Find contours
+    contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    # Sort contours by area (largest first)
+    contours = sorted(contours, key=cv2.contourArea, reverse=True)
+
+    sections = []
+    for contour in contours:
+        x, y, w, h = cv2.boundingRect(contour)
+        if w > 50 and h > 50:  # Filter out small contours
+            sections.append((x, y, w, h))
+
+    return sections
+
+def extract_text_from_section(image, section):
+    x, y, w, h = section
+    roi = image[y:y+h, x:x+w]
+
+    # Use Tesseract to extract text with custom configuration
+    custom_config = r'--oem 3 --psm 6 -l eng'
+    text = pytesseract.image_to_string(roi, config=custom_config)
+
+    return text
+
+def save_extracted_text(file_path, extracted_text):
+    with open(file_path, 'w', encoding='utf-8') as file:
+        file.write(extracted_text)
+    
+    messagebox.showinfo("Saved", f"Extracted text saved to {file_path}")
+
+def gui_main():
+    def upload_image():
+        file_path = filedialog.askopenfilename(
+            initialdir=os.path.join(os.path.expanduser("~"), "Desktop"),
+            title="Select an Image from Desktop",
+            filetypes=[("Image files", "*.jpg *.jpeg *.png *.bmp *.tiff")]
+        )
+        
+        if file_path:
+            try:
+                image = preprocess_image(file_path)
+                sections = segment_image(image)
+                extracted_text = ""
+                for section in sections:
+                    text = extract_text_from_section(image, section)
+                    if text:
+                        extracted_text += text + "\n" + "-" * 40 + "\n"
+
+                if extracted_text:
+                    text_area.delete('1.0', END)
+                    text_area.insert(END, extracted_text)
+                    display_image(file_path)
+                else:
+                    text_area.delete('1.0', END)
+                    text_area.insert(END, "No text extracted.")
+            except Exception as e:
+                text_area.delete('1.0', END)
+                text_area.insert(END, f"Error: {str(e)}")
+
+    def display_image(image_path):
+        img = Image.open(image_path)
+        img.thumbnail((250, 250))
+        img = ImageTk.PhotoImage(img)
+        panel.config(image=img)
+        panel.image = img
+
+    def save_text():
+        file_path = filedialog.asksaveasfilename(
+            defaultextension=".txt",
+            filetypes=[("Text files", ".txt"), ("All files", ".*")]
+        )
+        if file_path:
+            extracted_text = text_area.get("1.0", END)
+            save_extracted_text(file_path, extracted_text)
+
+    root = Tk()
+    root.title("OCR Application")
+    root.configure(bg='black')
+
+    frame = Frame(root, bg='black')
+    frame.pack(pady=10)
+
+    label = Label(frame, text="Upload an Image for OCR", bg='black', fg='white')
+    label.pack(pady=10)
+
+    upload_button = Button(frame, text="Upload Image", command=upload_image, bg='white', fg='black')
+    upload_button.pack(pady=5)
+
+    save_button = Button(frame, text="Save Extracted Text", command=save_text, bg='white', fg='black')
+    save_button.pack(pady=5)
+
+    text_frame = Frame(root)
+    text_frame.pack(fill=BOTH, expand=True, padx=10, pady=10)
+
+    scrollbar = Scrollbar(text_frame)
+    scrollbar.pack(side=RIGHT, fill=Y)
+
+    text_area = Text(text_frame, wrap='word', yscrollcommand=scrollbar.set, height=20, bg='black', fg='white', insertbackground='white')
+    text_area.pack(fill=BOTH, expand=True)
+    scrollbar.config(command=text_area.yview)
+
+    panel = Label(frame, bg='black')
+    panel.pack(pady=10)
+
+    root.mainloop()
+
+if __name__ == "__main__":
+    gui_main()