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face_recog_AI_model.py
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78 lines (65 loc) · 48.9 KB
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import face_recognition as fr
import cv2
import numpy as np
import os,shutil
#import google.colab.patches
'''
opencv-contrib-python-headless==4.6.0.66
opencv-python==4.6.0.66
opencv-python-headless==4.6.0.66
'''
#Here i have read the data from gogle drive
def get_encoded_faces():
encoded={}
for dirpath,dname,fname in os.walk("static/images/"):
for f in fname:
if f.endswith(".jpeg") or f.endswith(".jpg"):
face=fr.load_image_file("static/images/"+ f)
encoding=fr.face_encodings(face)[0]
encoded[f.split(".")[0]]=encoding
return (encoded)
#Here i have converted the image in array form of training data
x=get_encoded_faces()
#print(x)
# Here i am recognising the face of test data by providing certain data
def classify_face(im):
faces = get_encoded_faces()
faces_encoded = list(faces.values())
known_faces_names = list(faces.keys())
img = cv2.imread(im)
face_locations = fr.face_locations(img)
unknown_face_encodings = fr.face_encodings(img, face_locations)
face_names = []
for face_encoding in unknown_face_encodings:
name = "Unknown"
matches = fr.compare_faces(faces_encoded, face_encoding)
face_distances = fr.face_distance(faces_encoded, face_encoding)
best_match_index = np.argmin(face_distances)
if matches[best_match_index]:
name = known_faces_names[best_match_index]
face_names.append(name)
for (top, right, bottom, left), name in zip(face_locations, face_names):
cv2.rectangle(img, (left - 20, top - 20), (right + 20, bottom + 20), (255, 0, 0), 2)
cv2.rectangle(img, (left - 20, bottom - 15), (right + 20, bottom + 20), (255, 0, 0), cv2.FILLED)
cv2.putText(img, name, (left - 20, bottom + 15), cv2.FONT_HERSHEY_DUPLEX, 0.5, (255, 255, 255), 1)
while (True):
#cv2_imshow(img)
return (face_names)
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'
import base64
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'
#imgstring ='data:image/png;base64,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'
imgdata = base64.b64decode(imgstring)
from datetime import datetime
import os.path
directory = './studentimgs/'
now=datetime.now()
f_name = now.strftime("%d%m%Y %H%M%S")
filename = f_name+'.png'
filepath=os.path.join(directory, filename)
# print(f_name)
with open(filepath,'wb') as f:
f.write(imgdata)
f.close()
print("Done")
print(classify_face(filepath))