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April 11, 2018 11:40
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# -*- coding: utf-8 -*- | |
""" | |
Created on Thu Apr 5 17:23:53 2018 | |
@author: ADubey4 | |
""" | |
import cv2 | |
from pytesseract import pytesseract as pt | |
import pandas as pd | |
from PIL import Image | |
import sys | |
import pdf2image | |
import numpy as np | |
from signatureExtractor import getSignatureFromPage, getSignature | |
#from matplotlib import pyplot as plt | |
if sys.version_info[0] < 3: | |
from StringIO import StringIO | |
else: | |
from io import StringIO | |
pt.tesseract_cmd = r'C:\Program Files (x86)\Tesseract-OCR\tesseract' | |
file = r"C:\Users\file\path" | |
#search_word = "sincerely" | |
search_word = "signature" | |
signature_margin = (400, 400, 400, 400) # (left, top, right, bottom) | |
is_signature_margin_percentage = True # if true its percentage of the box dimensions, else the exact pixels | |
if(is_signature_margin_percentage): | |
signature_margin = [x/100.0 for x in signature_margin ] | |
if file.endswith(".pdf"): | |
doc_page_images = pdf2image.convert_from_path(file, dpi = 300) | |
else: | |
img = cv2.imread(file,cv2.COLOR_RGB2BGR) | |
doc_page_images=[img] | |
# img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) | |
def get_ocr_df(doc): | |
ret = pt.image_to_data(doc).lower() | |
TESTDATA = StringIO(ret) | |
return pd.read_csv(TESTDATA, sep=r"\t", engine='python').dropna(axis=0, how='any') | |
def clean_printed(im): | |
df = get_ocr_df(im) | |
print(df) | |
for i, row in df.iterrows(): | |
im[row.top:row.top + row.height+1, row.left:row.left + row.width+1] = 255 | |
return im | |
for page_no, doc in enumerate(doc_page_images): | |
df = get_ocr_df(doc) | |
signature_df = df[df['text'].str.contains(search_word)] | |
if type(doc) is np.ndarray: | |
x2_max = doc.shape[0] | |
y2_max = doc.shape[1] | |
doc_type = "np" | |
else: | |
x2_max = doc.size[0] | |
y2_max = doc.size[1] | |
doc_type = "pil" | |
for i, row in signature_df.iterrows(): | |
print(page_no, i) | |
if is_signature_margin_percentage : | |
x1 = row.left - int(signature_margin[0]*row.width) | |
y1 = row.top - int(signature_margin[1]*row.height) | |
x2 = row.left + row.width + int(signature_margin[2]*row.width) | |
y2 = row.top + row.height + int(signature_margin[3]*row.height) | |
else: | |
x1 = row.left - int(signature_margin[0]) | |
y1 = row.top - int(signature_margin[1]) | |
x2 = row.left + row.width + int(signature_margin[2]) | |
y2 = row.top + row.height + int(signature_margin[3]) | |
if x1 < 0: x1=0 | |
if y1 < 0: y1=0 | |
if x2 > x2_max: x2 = x2_max | |
if y2 > y2_max: x2 = y2_max | |
print(x1,y1, x2,y2) | |
if type(doc) is np.ndarray: | |
im = doc[y1:y2+1, x1:x2+1] | |
Image.fromarray(im).show() | |
else: | |
im = doc.crop((x1, y1, x2, y2)) | |
im.show() | |
im = clean_printed(np.array(im)) | |
Image.fromarray(im).show() | |
# signature = getSignatureFromPage(img = np.array(im)) | |
# signature = getSignature(img = signature) | |
# cv2.imshow('Signature'+str(i), signature) |
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