I'm using anaconda environment with python 3.7.7 everything was working properly, but I had to format my laptop and I installed the following libraries the same way I did before and they were installed, but when i run my code it's showing that the frame is not responding when the camera starts, opencv imshow is working, i think the problem is with the face recognition library.
the libraries i installed
conda install -c conda-forge opencv
conda install -c conda-forge dlib
pip install face_recognition
pip install imutils
and my code is:
from imutils.video import VideoStream
import face_recognition
import argparse
import imutils
import pickle
import time
import cv2
import numpy as np
import os
args = {
"encodings": "models/encodings/encodings.pickle",
"output": "output/"+outputFileName(),
"display": 1,
"detection_method": "cnn",
"confidence": 0.5,
"prototxt": "models/ssd/MobileNetSSD_deploy.prototxt",
"model": 'models/ssd/MobileNetSSD_deploy.caffemodel',
"use_gpu": 0
}
# load the known faces and embeddings
data = pickle.loads(open(args["encodings"], "rb").read())
vs = VideoStream(src=0).start()
writer = None
time.sleep(2.0)
fps = FPS().start()
names2=[]
t11=[]
no_names_pf=10
i1=10
vidsave=False
# loop over frames from the video file stream
while True:
frame = vs.read()
rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
rgb = imutils.resize(frame, width=750)
r = frame.shape[1] / float(rgb.shape[1])
# detect the (x, y)-coordinates of the bounding boxes
# corresponding to each face in the input frame, then compute
# the facial embeddings for each face
boxes = face_recognition.face_locations(rgb,
model=args["detection_method"])
encodings = face_recognition.face_encodings(rgb, boxes)
names = []
# loop over the facial embeddings
for encoding in encodings:
# attempt to match each face in the input image to our known
# encodings
matches = face_recognition.compare_faces(data["encodings"],
encoding)
name = "Unknown"
# check to see if we have found a match
if True in matches:
# find the indexes of all matched faces then initialize a
# dictionary to count the total number of times each face
# was matched
matchedIdxs = [i for (i, b) in enumerate(matches) if b]
counts = {}
# loop over the matched indexes and maintain a count for
# each recognized face face
for i in matchedIdxs:
name = data["names"][i]
counts[name] = counts.get(name, 0) + 1
# determine the recognized face with the largest number
# of votes (note: in the event of an unlikely tie Python
# will select first entry in the dictionary)
name = max(counts, key=counts.get)
# update the list of names
names.append(name)
print(names)
#___new code_____
names2.append(name)
#need to mod (capable of r of 1 person at the same time)
if len(names2)>no_names_pf:
confbool1=False
for i in range(no_names_pf):
i+=1
i=i*-1
if names2[-1] == names2[i-1]:
confbool1=True
else:
confbool1=False
break
if confbool1==True:
t11.append(name+'$$'+
str(datetime.datetime.now().strftime("%d-%m-%Y %H:%M:%S")))
if t11:
print(t11[-1])
#td01=frame[0:-2]
frameCopy=frame.copy()
# loop over the recognized faces
for ((top, right, bottom, left), name) in zip(boxes, names):
# rescale the face coordinates
top = int(top * r)
right = int(right * r)
bottom = int(bottom * r)
left = int(left * r)
# draw the predicted face name on the image
cv2.rectangle(frame, (left, top), (right, bottom),
(0, 255, 0), 2)
y0 = top - 15 if top - 15 > 15 else top + 15
cv2.putText(frame, name, (left, y0), cv2.FONT_HERSHEY_SIMPLEX,
0.75, (0, 255, 0), 2)
# if the video writer is None *AND* we are supposed to write
# the output video to disk initialize the writer
if writer is None and args["output"] is not None:
fourcc = cv2.VideoWriter_fourcc(*"MJPG")
writer = cv2.VideoWriter(args["output"], fourcc, 20,
(frame.shape[1], frame.shape[0]), True)
# if i1%10 == 0 :
# print(vidsave)
# print(label)
# print('person' in label)
#i1=i1+1
vidsave=False
# check to see if we are supposed to display the output frame to
# the screen
if args["display"] > 0:
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
#__________________________________________
fps.update()
# stop the timer and display FPS information
fps.stop()
print("[INFO] elasped time: {:.2f}".format(fps.elapsed()))
print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
cv2.destroyAllWindows()
vs.stop()
if writer is not None:
writer.release()
#___________________________________________________________________
# report handeling
appendtxt("output/"+datetime.datetime.now()
.strftime("%d-%m-%Y")+" report.txt",'a
')
this_year=datetime.datetime.now().strftime("%Y")
this_month=datetime.datetime.now().strftime("%m")
this_day=datetime.datetime.now().strftime("%d")
# if not os.path.exists('output/'+this_year):
# os.makedirs('output/'+this_year)
# if not os.path.exists('output/'+this_year+'/'+this_month):
# os.makedirs('output/'+this_year+'/'+this_month)
# if not os.path.exists('output/'+this_year+'/'+this_month+'/'+this_day):
# os.makedirs('output/'+this_year+'/'+this_month+'/'+this_day)
#image = cv2.imread("C:/Users/anwar/Desktop/lllsky.png")
# cv2.imshow("Image", frame)
# cv2.imwrite('output/aa.jpg', frame)
# cv2.waitKey(0)
# fc = frameCopy[top-50:bottom+50 , left-50:right+50 ]
# cv2.imshow("fc", fc)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
