Files changed (1) hide show
  1. app.py +19 -4
app.py CHANGED
@@ -32,7 +32,7 @@ import docx2txt
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  from PIL import Image
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  from PyPDF2 import PdfFileReader
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  import pdfplumber
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-
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  # NLP Pkgs
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  from textblob import TextBlob
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  import spacy
@@ -41,6 +41,7 @@ import requests
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  import cv2
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  import numpy as np
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  import pytesseract
 
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  #pytesseract.pytesseract.tesseract_cmd = r"./Tesseract-OCR/tesseract.exe"
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  from PIL import Image
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  def read_pdf(file):
@@ -49,14 +50,17 @@ def read_pdf(file):
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  all_page_text = ""
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  for i in range(count):
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  page = pdfReader.getPage(i)
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- all_page_text += page.extractText()
 
 
 
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  return all_page_text
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  #def read_pdf_with_pdfplumber(file):
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  # with pdfplumber.open(file) as pdf:
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  # page = pdf.pages[0]
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- # return page.extract_text()s
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  st.title("Streamlit NLP APP")
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  @st.experimental_singleton
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  def text_analyzer(my_text):
@@ -107,7 +111,18 @@ def main():
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  img = Image.open(uploaded_photo)
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  img = img.save("img.png")
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  img = cv2.imread("img.png")
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- text = pytesseract.image_to_string(img, lang="ben") if st.checkbox("Mark to see Bangla Image's Text") else pytesseract.image_to_string(img)
 
 
 
 
 
 
 
 
 
 
 
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  st.success(text)
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  elif camera_photo:
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  img = Image.open(camera_photo)
 
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  from PIL import Image
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  from PyPDF2 import PdfFileReader
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  import pdfplumber
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+ from line_cor import mark_region
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  # NLP Pkgs
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  from textblob import TextBlob
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  import spacy
 
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  import cv2
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  import numpy as np
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  import pytesseract
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+
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  #pytesseract.pytesseract.tesseract_cmd = r"./Tesseract-OCR/tesseract.exe"
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  from PIL import Image
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  def read_pdf(file):
 
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  all_page_text = ""
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  for i in range(count):
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  page = pdfReader.getPage(i)
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+ image_name = "Page_" + str(i) + ".jpg"
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+ page.save(image_name, "JPEG")
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+ text = pytesseract.image_to_string(image_name, lang="ben") if st.checkbox("Mark to see Bangla Image's Text") else pytesseract.image_to_string(image_name)
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+ all_page_text += text + " " #page.extractText()
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  return all_page_text
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  #def read_pdf_with_pdfplumber(file):
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  # with pdfplumber.open(file) as pdf:
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  # page = pdf.pages[0]
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+ # return page.extract_text()
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  st.title("Streamlit NLP APP")
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  @st.experimental_singleton
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  def text_analyzer(my_text):
 
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  img = Image.open(uploaded_photo)
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  img = img.save("img.png")
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  img = cv2.imread("img.png")
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+ # get co-ordinates to crop the image
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+ image, lc = mark_region(img)
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+ c = lc[1]
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+ # cropping image img = image[y0:y1, x0:x1]
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+ img = image[c[0][1]:c[1][1], c[0][0]:c[1][0]]
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+ plt.figure(figsize=(10,10))
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+ plt.imshow(img)
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+ # convert the image to black and white for better OCR
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+ ret,thresh1 = cv2.threshold(img,120,255,cv2.THRESH_BINARY)
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+ # pytesseract image to string to get results
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+ text = str(pytesseract.image_to_string(thresh1, config='--psm 6',lang="ben")) if st.checkbox("Bangla") else str(pytesseract.image_to_string(thresh1, config='--psm 6'))
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+ #text = pytesseract.image_to_string(img, lang="ben") if st.checkbox("Mark to see Bangla Image's Text") else pytesseract.image_to_string(img)
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  st.success(text)
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  elif camera_photo:
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  img = Image.open(camera_photo)