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process.py
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process.py
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#new version soon
import face_recognition as frc
import os
import cv2
import numpy as np
from PIL import *
import json
import time
from PIL import ImageFont
from PIL import ImageDraw
import argparse
loading = 0
limite = 0
time_tk = []
#Load the image
def load(path):
global loading
global input,face,face_l
input = frc.load_image_file(path)
face = frc.face_locations(input,model="hog")
face_l = frc.face_landmarks(input,model="large")
loading = loading + 20
def start(path):
global loading
face_errors = False
for i in face_l:
chin = i.get("chin")
left_eyebrow = i.get("left_eyebrow")
right_eyebrow = i.get("right_eyebrow")
nose_bridge = i.get("nose_bridge")
nose_tip = i.get("nose_tip")
left_eye = i.get("left_eye")
right_eye = i.get("right_eye")
top_lip = i.get("top_lip")
bottom_lip = i.get("bottom_lip")
points1 = list()
for points in chin,left_eyebrow,right_eyebrow,nose_bridge,nose_tip,left_eye,right_eye,top_lip,bottom_lip:
for x in range(0,len(points)):
x1,y1 = points[x]
points1.append((x1,y1))
for faces in face:
(x,y,w,h) = faces
loading = loading + 20
#Box around the face
if len(face) == 1 :
back = Image.open(path)
foreground = Image.open("./src/images/imageedit_1_2789986383(1).png").convert("RGBA")
foreground = foreground.resize((int(w-x+(w-x)/3),int(w-x+(w-x)/3)))
h1,w1=foreground.size
back.paste(foreground, (int(h-h/55),int(x-h/55)), foreground)
font = ImageFont.truetype("./src/fonts/neuropolitical rg.ttf", int(w/15))
im = cv2.cvtColor(np.array(back),cv2.COLOR_RGB2BGR)
#LANDMARKS_TRIANGLES
loading = loading + 30
def rect_contains(rect, point) :
if point[0] < rect[0] :
return False
elif point[1] < rect[1] :
return False
elif point[0] > rect[2] :
return False
elif point[1] > rect[3] :
return False
return True
# Draw a point
if back.width < 800:
lfont = 1
rcircle = 2
else:
lfont = 2
rcircle = 4
def draw_point(img, p, color ) :
cvc = cv2.circle( img, p,rcircle, color, cv2.FILLED, cv2.LINE_AA, 0 )
# Draw delaunay triangles
def draw_delaunay(img, subdiv, delaunay_color ) :
triangleList = subdiv.getTriangleList();
size = img.shape
r = (0, 0, size[1], size[0])
for t in triangleList :
pt1 = (t[0], t[1])
pt2 = (t[2], t[3])
pt3 = (t[4], t[5])
if rect_contains(r, pt1) and rect_contains(r, pt2) and rect_contains(r, pt3) :
cv2.line(img, pt1, pt2, delaunay_color, lfont, cv2.LINE_AA, 0)
cv2.line(img, pt2, pt3, delaunay_color, lfont, cv2.LINE_AA, 0)
cv2.line(img, pt3, pt1, delaunay_color, lfont, cv2.LINE_AA, 0)
animate = True
# Define colors for drawin
delaunay_color = (25,0,0)
points_color = (0, 0, 255)
img = im
# Keep a copy around
img_orig = img.copy();
# Rectangle to be used with Subdiv2D
size = img.shape
rect = (0, 0, size[1], size[0])
subdiv = cv2.Subdiv2D(rect);
for p in points1 :
subdiv.insert(p)
if animate :
img_copy = img_orig.copy()
draw_delaunay( img_copy, subdiv, (255,219,0) );
imw,imh,c = img_copy.shape
# Draw points
for p in points1 :
draw_point(img_copy, p, (255,255,255))
loading = loading + 30
img_cop = cv2.cvtColor(img_copy,cv2.COLOR_BGR2RGB)
cv2.imwrite("./src/images/id2_.png",img_copy)
elif len(face) == 0:
face_errors = None
else:
face_errors = True
return face_errors
#Compare the face encodings
def search(inp):
global id_name
id_name = []
global time_tk
time_tk = []
global limite
limite = len(os.listdir("./data/"))
inp = frc.load_image_file(inp)
face = frc.face_locations(inp,model="hog")
enc1 = frc.face_encodings(inp,face)
for files in os.listdir("./data/"):
start = time.time()
for np_enc in os.listdir(f"./data/{files}/"):
if np_enc == "enc.npy":
enc2 = np.load(f"./data/{files}/enc.npy")
predict = frc.compare_faces(enc1,enc2,0.6)
if str(predict[0]) == "True":
id_name.append(files)
final = time.time() - start
time_tk.append(final)
#Create the Id Card
def id_card():
try:
id = Image.open("./data/"+str(id_name[0])+"/"+str(id_name[0])+".jpg").convert("RGBA").resize((200,200))
id_b = Image.open("./src/images/imageedit_3_5670490135.png")
id_b = id_b.resize((132,142))
id = id.resize((110,110))
im2 = Image.open("./src/images/id3.png")
w2,h2 = im2.size
im2.paste(id,(int(w2/4.8),int(h2/4.5)),id)
im2.paste(id_b,(int(w2/5.2),int(h2/5.5)),id_b)
draw = ImageDraw.Draw(im2)
font = ImageFont.truetype("./src/fonts/neuropolitical rg.ttf", 20)
font2 = ImageFont.truetype("./src/fonts/neuropolitical rg.ttf", 19)
with open(f"./data/{str(id_name[0])}/data.json","r") as read:
data = json.load(read)
draw.text((int(w2/2.35),int(h2/5)+15),"Full Name : " + str(data['name']),(153, 242, 255),font=font)
draw.text((int(w2/2.35),int((h2/5)+45)),"D.O.B : "+str(data['dob']),(153, 242, 255),font=font)
draw.text((int(w2/2.35),int((h2/5)+75)),"Country/City: "+str(data['cc']),(153, 242, 255),font=font)
draw.text((int(w2/2.35),int((h2/5)+105)),"Gender : "+str(data['gen']) ,(153, 242, 255),font=font)
draw.text((int(w2/5),int((h2/5)+170)),"Job : "+str(data['job']) ,(153, 242, 255),font=font2)
draw.text((int(w2/5),int((h2/5)+195)),"Work location : "+str(data['job_loc']) ,(153, 242, 255),font=font2)
draw.text((int(w2/5),int((h2/5)+220)),"Phone number 1 : "+str(data['phone_n1']) ,(153, 242, 255),font=font2)
draw.text((int(w2/5),int((h2/5)+245)),"Phone number 2 : "+str(data['phone_n2']) ,(153, 242, 255),font=font2)
draw.text((int(w2/5),int((h2/5)+270)),"Residence address : "+str(data['addr']) ,(153, 242, 255),font=font2)
draw.text((int(w2/5),int((h2/5)+295)),"E-mail : "+str(data['email']) ,(153, 242, 255),font=font2)
im2.save("./src/images/id2.png")
except:
return False