upgrade

.gitignore

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-**/__pycache__/

doc.md

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-# Extract Text from photo

gardio.py

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-import gradio as gr
-from PIL import Image
-import pytesseract
-
-custom_css = """
-    .big-font textarea {
-        font-size: 20px !important;
-    }
-"""
-
-def extract_text(image):
-    # Convert the image to text using pytesseract
-    text = pytesseract.image_to_string(image)
-    return text
-
-# Create the Gradio interface
-iface = gr.Interface(
-    fn=extract_text,
-    inputs=gr.Image(type="pil"),  # Accept PIL images directly
-    outputs=gr.Textbox(lines=20,
-                       max_lines=10,
-                       label='Extracted Text',
-                       elem_classes=["big-font"]
-                       ),
-    title="Text Extraction",
-    description="Upload an image to extract text",
-    allow_flagging='never',
-    css=custom_css
-)
-
-# Launch the app
-iface.launch()

main.py

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-import pytesseract
-from PIL import Image 
-
-
-def extract_text(image_path):
-    img = Image.open(image_path)
-    et = pytesseract.image_to_string(img)
-
-    return et 
-
-
-
-# if __name__ == "__main__":
-#     text = extract_text(image_path="/home/manish/Desktop/projects/etfp/data/WhatsApp Image 2025-09-13 at 19.01.52.jpeg")
-#     print(text)
-

test.py

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-import cv2
-import pytesseract
-
-myconfig = r"--psm 11 --oem 3"
-
-def extract_text(image_path):
-
-  #Loading image in CV2 format
-  img = cv2.imread(image_path)
-
-  #Image preprocessing
-  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-  cv2.imwrite("temp/gray.png", gray)
-  blur = cv2.GaussianBlur(gray, (7,7), 0)
-  cv2.imwrite("temp/blur.png", blur)
-
-  thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
-  kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,13))
-  dilate = cv2.dilate(thresh, kernel, iterations=1)
-
-  #Finding Contours for creating boundaries
-  cnts = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-  cnts = cnts[0] if len(cnts) == 2 else cnts[1]
-  cnts = sorted(cnts, key=lambda x: cv2.boundingRect(x)[0])
-
-  for c in cnts:
-    x, y, w, h = cv2.boundingRect(c)
-    if h > 50 and w > 10:
-      cv2.rectangle(img, (x,y), (x+w, y+h), (36,200,12), 2)
-
-  cv2.imwrite("temp/boxes.png", img)
-
-  # Text extraction
-  text = pytesseract.image_to_string(gray,config=myconfig)
-
-  print("Extracted Text:\n", text)
-  return img, text