Vehicle-Anti-Theft-Face-Rec.../Facial_Recognition_Software.py

103 lines
2.9 KiB
Python

import sys
import os
import cv2
import numpy as np
from glob import glob
from skimage import io
def face_detector_haarcascade(image):
grey = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
resize_fx = 1
resize_fy = 1
grey = cv2.resize(grey, dsize=None, fx=resize_fx, fy=resize_fy, interpolation = cv2.INTER_AREA)
pwd = sys.path[0]
classfier = cv2.CascadeClassifier(pwd + "/Facial_models/haarcascade_frontalface_alt2.xml")
faceRects = classfier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=1, minSize=(16, 16))
if len(faceRects) > 0:
for faceRect in faceRects:
x, y, w, h = faceRect
x = int(x/resize_fx)
y = int(y/resize_fy)
w = int(w/resize_fx)
h = int(h/resize_fy)
cv2.rectangle(image, (x - 10, y - 10), (x + w + 10, y + h + 10), (0, 255, 0), 5)
return image
def face_detector_ssd(image):
pwd = sys.path[0]
net = cv2.dnn.readNetFromCaffe(pwd+"/Facial_models/deploy.prototxt", pwd+"/Facial_models/res10_300x300_ssd_iter_140000_fp16.caffemodel")
resize = (300, 300)
confidence_thres = 0.65
blob = cv2.dnn.blobFromImage(cv2.resize(image, dsize=resize), 1.0, resize, (104.0, 177.0, 123.0))
# blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))
net.setInput(blob)
detections = net.forward()
h,w,c=image.shape
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > confidence_thres:
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
text = "{:.2f}%".format(confidence * 100)
y = startY - 10 if startY - 10 > 10 else startY + 10
cv2.rectangle(image, (startX, startY), (endX, endY),(0, 255,0), 5)
cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 1.00, (0, 255, 0), 3)
return image
if __name__=="__main__":
cameraCapture = cv2.VideoCapture(1)
success, frame = cameraCapture.read()
while success and cv2.waitKey(1) == -1:
success, frame = cameraCapture.read()
face_detector_ssd(frame)
cv2.imshow("video", frame)
cameraCapture.release()
cv2.destroyAllWindows()
# image process (keep it in case if needed)
'''
image_name = "8.jpg"
split_name = image_name.split(".")
image_read_path = sys.path[0]+"/Facial_test_images/"+image_name
image_save_path = sys.path[0]+"/Facial_test_images/output/"+split_name[0]+"_result."+split_name[1]
image = cv2.imread(image_read_path)
image = face_detector_ssd(image)
image = face_detector_haarcascade(image)
print(image_save_path)
cv2.imwrite(image_save_path, image)
cv2.imshow("result", image)
cv2.waitKey()
cv2.destroyAllWindows()
'''