我尝试了一种简化的方法，如p.Ro在他的回答中提到的，进程写入输出队列，但是由于所有进程同时写入队列，队列大部分时间都被锁定了。(只是我的猜测)我可能做错了什么。

最后我用了管子。

密码太恶心了。但如果几个小时前我是我的话。我还是很高兴能找到一个不费吹灰之力的例子。from multiprocessing import Process, Queue, Manager,Pipe

import multiprocessing

import face_recognition as fik

import cv2

import time

video_input = 0

obama_image = fik.load_image_file("obama.png")

obama_face_encoding = fik.face_encodings(obama_image)[0]

quality = 0.7

def f(id,fi,fl):

import face_recognition as fok

while True:

small_frame = fi.get()

print("running thread"+str(id))

face_locations = fok.face_locations(small_frame)

if(len(face_locations)>0):

print(face_locations)

for (top7, right7, bottom7, left7) in face_locations:

small_frame_c = small_frame[top7:bottom7, left7:right7]

fl.send(small_frame_c)

fps_var =0

if __name__ == '__main__':

multiprocessing.set_start_method('spawn')

# global megaman

with Manager() as manager:

video_capture = cv2.VideoCapture(video_input)

fi = Queue(maxsize=14)

threads = 8

proc = []

parent_p = []

thread_p = []

# procids = range(0,threads)

for t in range(0,threads):

p_t,c_t = Pipe()

parent_p.append(p_t)

thread_p.append(c_t)

print(t)

proc.append(Process(target=f, args=(t,fi,thread_p[t])))

proc[t].start()

useframe = False

frame_id = 0

while True:

# Grab a single frame of video

ret, frame = video_capture.read()

effheight, effwidth = frame.shape[:2]

if effwidth < 20:

break

# Resize frame of video to 1/4 size for faster face recognition processing

xxx = 930

yyy = 10/16 #0.4234375

small_frame = cv2.resize(frame, (xxx, int(xxx*yyy)))

if frame_id%2 == 0:

if not fi.full():

fi.put(small_frame)

print(frame_id)

cv2.imshow('Video', small_frame)

print("FPS: ", int(1.0 / (time.time() - fps_var)))

fps_var = time.time()

#GET ALL DETECTIONS

for t in range(0,threads):

if parent_p[t].poll():

small_frame_c = parent_p[t].recv()

cv2.imshow('recc', small_frame_c)

height34, width34 = small_frame_c.shape[:2]

# print fsizeee

if(width34<20):

print("face 2 small")

print(width34)

break

face_encodings_cam = fik.face_encodings(small_frame_c,[(0, width34, height34, 0)])

match = fik.compare_faces([obama_face_encoding], face_encodings_cam[0])

name = "Unknown"

if match[0]:

name = "Barack"

print(name)

break

frame_id += 1

# Hit 'q' on the keyboard to quit!

if cv2.waitKey(1) & 0xFF == ord('q'):

break