Face Recognition Added

Aadhaar.py

@@ -1,25 +1,32 @@
-#!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 """
-Created on Thu Mar 20 00:16:35 2020
+Created on Fri Apr 24 20:01:19 2020
 
-@author: utsav
+@author: Kshitija Surange
 """
 
+
 import cv2
 from PIL import Image
 import pytesseract
 from pytesseract import Output
 import re
+
+import numpy as np
+import math
+from scipy import ndimage
+import face_recognition
+import uuid
 import os
 
 class Aadhaar_Card():
     #Constructor
     def __init__(self,config = {'orient' : True,'skew' : True,'crop': True,'contrast' : True,'psm': [3,4,6],'mask_color': (0, 165, 255), 'brut_psm': [6]}):
         self.config = config
-    # Validates Aadhaar card numbers using Verhoeff Algorithm.
+        self.uuid=uuid.uuid4();
+    # Validates Aadhar card numbers using Verhoeff Algorithm.
     # Fails if the fake number is generated using same Algorithm.
-    def validate(self,aadhaarNum):
+    def validate(self,aadharNum):
 
         mult = [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 0, 6, 7, 8, 9, 5], [2, 3, 4, 0, 1, 7, 8, 9, 5, 6],
             [3, 4, 0, 1, 2, 8, 9, 5, 6, 7], [4, 0, 1, 2, 3, 9, 5, 6, 7, 8], [5, 9, 8, 7, 6, 0, 4, 3, 2, 1],
@@ -32,13 +39,13 @@ def validate(self,aadhaarNum):
 
 
         try:
-            i = len(aadhaarNum)
+            i = len(aadharNum)
             j = 0
             x = 0
 
             while i > 0:
                 i -= 1
-                x = mult[x][perm[(j % 8)][int(aadhaarNum[i])]]
+                x = mult[x][perm[(j % 8)][int(aadharNum[i])]]
                 j += 1
             if x == 0:
                 return 1 
@@ -56,6 +63,8 @@ def extract(self, path):  #("path of input image")
         self.image_path = path
         self.read_image_cv()
         if self.config['orient']:
+            self.cv_img = self.rotate(self.cv_img)
+            '''
 
             try:
                 self.cv_img = self.rotate(self.cv_img)
@@ -67,6 +76,21 @@ def extract(self, path):  #("path of input image")
                 os.remove('1_temp.png')
 
         self.pil_img = self.pil_img.convert('RGBA')
+        '''
+
+        '''
+
+            try:
+                self.cv_img = self.rotate(self.cv_img)
+            except:
+                self.read_image_pil()
+            else:
+                self.cv_img.save('1_temp.png')
+                self.pil_img = Image.open('1_temp.png')     
+                os.remove('1_temp.png')
+
+        self.pil_img = self.pil_img.convert('RGBA')
+        '''
 
         if self.config['skew']:
             print("skewness correction not available")
@@ -75,46 +99,51 @@ def extract(self, path):  #("path of input image")
             print("Smart Crop not available")
 
         if self.config['contrast']:
-            self.pil_img  = self.contrast_image(self.pil_img )
+
+            self.cv_img  = self.contrast_image(self.cv_img)
+            #self.pil_img  = self.contrast_image(self.pil_img )
+
             print("correcting contrast")
 
-        aadhaars = set()
+        aadhars = set()
         for i in range(len(self.config['psm'])):
-            t = self.text_extractor(self.pil_img,self.config['psm'][i])
-            anum = self.is_aadhaar_card(t)
+            t = self.text_extractor(self.cv_img,self.config['psm'][i])
+
+            anum = self.is_aadhar_card(t)
+
             uid = self.find_uid(t)
 
 
             if anum != "Not Found" and len(uid) == 0:
                 if len(anum) - anum.count(' ') == 12:
-                   aadhaars.add(anum.replace(" ", ""))
+                   aadhars.add(anum.replace(" ", ""))
             if anum == "Not Found" and len(uid) != 0:
 
-                aadhaars.add(uid[0].replace(" ", ""))
+                aadhars.add(uid[0].replace(" ", ""))
             if anum != "Not Found" and len(uid) != 0:
                 if len(anum) - anum.count(' ') == 12:
-                   aadhaars.add(anum.replace(" ", ""))
+                   aadhars.add(anum.replace(" ", ""))
                 #print(uid[0].strip())
-                aadhaars.add(uid[0].replace(" ", ""))
+                aadhars.add(uid[0].replace(" ", ""))
 
-        return list(aadhaars)
+        return list(aadhars)
 
-    def mask_image(self, path, write, aadhaar_list):
-        #print("Read Path => ", path, " write path => ",write, "aadhaar list =>",aadhaar_list)
+    def mask_image(self, path, write, aadhar_list):
+        #print("Read Path => ", path, " write path => ",write, "aadhar list =>",aadhar_list)
         self.mask_count = 0
         self.mask = cv2.imread(str(path), cv2.IMREAD_COLOR)
         for j in range(len(self.config['psm'])):
-            for i in range(len(aadhaar_list)):
-                #print(" Runing mode: Aadhaar number:",aadhaar_list[i]," PSM => ",self.config['psm'][j])
-                if (self.mask_aadhaar(aadhaar_list[i],write,self.config['psm'][j]))>0:
+            for i in range(len(aadhar_list)):
+                #print(" Runing mode: Aadhar number:",aadhar_list[i]," PSM => ",self.config['psm'][j])
+                if (self.mask_aadhar(aadhar_list[i],write,self.config['psm'][j]))>0:
                     self.mask_count = self.mask_count + 1
                 #print(" :\/ ",self.mask_count)
 
         #print("Final Mask Count =>",self.mask_count)
         cv2.imwrite(write,self.mask)
         return self.mask_count
 
-    def mask_aadhaar(self, uid, out_path, psm):
+    def mask_aadhar(self, uid, out_path, psm):
         d = self.box_extractor(self.mask, psm)
         n_boxes = len(d['level'])
         color = self.config['mask_color'] #BGR
@@ -131,10 +160,12 @@ def mask_aadhaar(self, uid, out_path, psm):
 
     def read_image_cv(self):
         self.cv_img = cv2.imread(str(self.image_path), cv2.IMREAD_COLOR)
-
+
+    '''
     def read_image_pil(self):
         self.pil_img = Image.open(self.image_path)
-
+    '''
+
     def mask_nums(self, input_file, output_file):
         img = cv2.imread(str(input_file), cv2.IMREAD_COLOR)
         for i in range(len(self.config['brut_psm'])):      #'brut_psm': [6]
@@ -153,48 +184,93 @@ def mask_nums(self, input_file, output_file):
 
         return "Done"
 
+
+    def rotate_only(self, img, angle_in_degrees):
+        self.img = img
+        self.angle_in_degrees = angle_in_degrees
+        rotated = ndimage.rotate(self.img, self.angle_in_degrees)
+        return rotated
 
+    def is_image_upside_down(self, img):
+        self.img = img
+        face_locations = face_recognition.face_locations(self.img)
+        encodings = face_recognition.face_encodings(self.img, face_locations)
+        image_is_upside_down = (len(encodings) == 0)
+        return image_is_upside_down
 
-    # Corrects orientation of image using tesseract OSD if rotation Angle is < 100.
-    def rotate(self,image, center = None, scale = 1.0):
-
-        rotate_angle=int(re.search('(?<=Rotate: )\d+', pytesseract.image_to_osd(image)).group(0))
-
-        if rotate_angle > 100:
-
-            img = Image.fromarray(image, 'RGB')
-            b, g, r = img.split()
-            img = Image.merge("RGB", (r, g, b))
-            return img
+    ''' 
+    def save_image(self, img):
+        self.img = img
+        cv2.imwrite('orientation_corrected.jpg', self.img)
 
+
+    def display(self, img, frameName="OpenCV Image"):
+        self.img = img
+        self.frameName = frameName
+        h, w = self.img.shape[0:2]   
+        neww = 800
+        newh = int(neww*(h/w))
+        self.img = cv2.resize(self.img, (neww, newh))
+        cv2.imshow(self.frameName, self.img)
+        cv2.waitKey(0)
+    '''
+
+    # Corrects orientation of image using tesseract OSD if rotation Angle is < 100.
+    def rotate(self,img):
+        #def orientation_correction(img): #, save_image = False):
+        # GrayScale Conversion for the Canny Algorithm 
+        self.img = img
+        img_gray = cv2.cvtColor(self.img, cv2.COLOR_BGR2GRAY) 
+        #self.display(img_gray)
+        # Canny Algorithm for edge detection was developed by John F. Canny not Kennedy!! :)
+        img_edges = cv2.Canny(img_gray, 100, 100, apertureSize=3)
+        #self.display(img_edges)
+        # Using Houghlines to detect lines
+        lines = cv2.HoughLinesP(img_edges, 1, math.pi / 180.0, 100, minLineLength=100, maxLineGap=5)
+        img_copy = self.img.copy()
+        for x in range(0, len(lines)):
+            for x1,y1,x2,y2 in lines[x]:
+                cv2.line(img_copy,(x1,y1),(x2,y2),(0,255,0),2)
+        #cv2.imshow('hough',img_copy)
+        #cv2.waitKey(0)
+
+        angles = []
+        for x1, y1, x2, y2 in lines[0]:
+            angle = math.degrees(math.atan2(y2 - y1, x2 - x1))
+            angles.append(angle)
+
+        # Getting the median angle
+        median_angle = np.median(angles)
+        # Rotating the image with this median angle
+        img_rotated = self.rotate_only(self.img, median_angle)
+        #self.display(img_rotated)
+
+        if self.is_image_upside_down(img_rotated):
+            print("rotate to 180 degree")
+            angle = -180
+            img_rotated_final = self.rotate_only(img_rotated, angle)
+            #self.save_image(img_rotated_final)
+            #self.display(img_rotated_final)
+            if self.is_image_upside_down(img_rotated_final):
+                print("Kindly check the uploaded image, face encodings still not found!")
+                return img_rotated
+            else:
+                print("image is now straight")
+                return img_rotated_final
         else:
-            angle=360-int(re.search('(?<=Rotate: )\d+', pytesseract.image_to_osd(image)).group(0))
-            (h, w) = image.shape[:2]
+            #self.display(img_rotated)
+            print("image is straight")
+            return img_rotated
 
-            if center is None:
-                center = (w / 2, h / 2)
-
-            # Perform the rotation
-            M = cv2.getRotationMatrix2D(center, angle, scale)
-            rotated = cv2.warpAffine(image, M, (w, h))
-
-            img = Image.fromarray(rotated, 'RGB')
-            b, g, r = img.split()
-            img = Image.merge("RGB", (r, g, b))
-
-            return img
 
     # Turns images BnW using pixels, didn't have much success with this and skipped in final production 
     def contrast_image(self, img):
-        pix = img.load()
-        # taking pixel value for using in ocr
-        for y in range(img.size[1]):
-            for x in range(img.size[0]):
-                if pix[x, y][0] < 102 or pix[x, y][1] < 102 or pix[x, y][2] < 102:
-                    pix[x, y] = (0, 0, 0, 255)
-                else:
-                    pix[x, y] = (255, 255, 255, 255)
-        return img
+        self.img = img
+        gray = cv2.cvtColor(self.img, cv2.COLOR_BGR2GRAY)
+        #gray = cv2.bitwise_not(gray)
+        thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
+        #self.display(thresh)
+        return thresh
 
     # Extracts Texts from images
     def text_extractor(self, img, psm):
@@ -224,18 +300,17 @@ def find_uid(self,text2):
             pass
         return list(uid)
 
-    #Function to validate if an image contains text showing its an aadhaar card
-    def is_aadhaar_card(self, text):
+    #Function to validate if an image contains text showing its an aadhar card
+    def is_aadhar_card(self, text):
                res=text.split()
-               aadhaar_number=''
+               aadhar_number=''
                for word in res:
                   if len(word) == 4 and word.isdigit():
-                      aadhaar_number=aadhaar_number  + word + ' '
-               if len(aadhaar_number)>=14:
-                   return aadhaar_number
+                      aadhar_number=aadhar_number  + word + ' '
+               if len(aadhar_number)>=14:
+                   return aadhar_number
 
                else:
 
                     return "Not Found"
-
-
+

Dockerfile

@@ -1,4 +1,3 @@
-
 FROM debian:buster-slim as buildstage
 LABEL maintainer="Utsav Mishra <https://festivitymishra.github.io/>"
 
@@ -14,15 +13,16 @@ RUN apt-get update && \
 # Build Python APP Here
 RUN mkdir aadhaar_ocr_masking
 
+COPY requirements.txt /aadhaar_ocr_masking/requirements.txt
+RUN pip install -r /aadhaar_ocr_masking/requirements.txt
 
 COPY Aadhaar.py /aadhaar_ocr_masking/Aadhaar.py
 COPY app.py /aadhaar_ocr_masking/app.py
-COPY requirements.txt /aadhaar_ocr_masking/requirements.txt
 
-RUN cd aadhaar_ocr_masking && \
-    pip install -r requirements.txt
+RUN mkdir /aadhaar_ocr_masking/temp
+RUN mkdir /aadhaar_ocr_masking/public
 
-WORKDIR /aadhaar_ocr_masking
+COPY public/* /aadhaar_ocr_masking/public/
 
+WORKDIR /aadhaar_ocr_masking
 CMD ["python", "app.py"]
-