Saludes soy nuevo, estoy trabajando sobre reconocimiento de rostros y ando buscando apoyo
try again in english, please.
also, please explain, what you’ve tried, so far,
and what the current problem is
1 Like
programa
#…importar librerias
import os
import numpy as np
import cv2
#…importamos las fotos tomadas
nombre = “hola”
direccion = “C:/Users/valme/OneDrive/protocolo de escuelas/proyectos python/same/deteccion de rostro y cubre bocas/fotos”
lista = os.listdir(direccion)
etiquetas = []
rostros = []
cont = 0
for nameDir in lista:
nombre = direccion + “/” + nameDir # leer las fotos de los rostros
for fileName in os.listdir(nombre):
etiquetas.append(cont) #asignamos las etiquetas
rostros.append(cv2.imread(nombre + "/" + fileName, 0))
cont = cont + 1
print(etiquetas)
#…creamos el modelo
reconocimiento = cv2.face.LBPHFaceRecognizer_create()
#…Entrenamos el modelo
reconocimiento.train(rostros, np.array(etiquetas))
#…guardamos el modelo
reconocimiento.write(ModeloEntrenando.xml)
print(“Modelo Creado”)
error
Traceback (most recent call last):
File “C:\Users\valme\OneDrive\protocolo de escuelas\proyectos python\same\deteccion de rostro y cubre bocas\entrenador.py”, line 29, in
reconocimiento.train(rostros, np.array(etiquetas))
cv2.error: OpenCV(4.5.5) D:\a\opencv-python\opencv-python\opencv\modules\core\src\matrix.cpp:250: error: (-215:Assertion failed) s >= 0 in function ‘cv::setSize’
Enviaste
Hello from Honduras, the problem I have is that I managed to take the photos but when I load to create the ´reconocimiento.train(rostros, np.array(etiquetas))´ I cannot create the model *.xml and that is why I am looking for it the support to see if they can upload my code and see if it’s a problem with my pc or a general problem and I can’t move on from there.
I put add where I’m going in the trainer and the error it gives me
i recommend you to use newer and better OpenCV: DNN-based Face Detection And Recognition
you probably tried to load an image, but it failed (it is empty / invalid)
please add a check after cv2.imread()
Thanks for the quick response and how would you go about letting the system know that there is an invalid file and move on from this
again, add a check after the imread() and only proceed if the image is not none
hello thank you very much with the guide you gave me I found the problems, but I don’t know how to write the instruction, add the code as I think it could be for verification use an imshow to see where that file was
if rostros == None: # wrong path ? not an image ?
rostros.append(cv2.imread(nombre + “/” + fileName, 0))
else:
continue
Greetings from Honduras bothering again.
I managed to make the part where I create the model work and it was what I got was a file that was not a photo.
but now I have 100 folders with photos ready when I run the file with 10 folders it works but when I load the *.xml file with the 100 folders it just doesn’t activate the camera for detection when it’s a small file it works.
it has opencv folder limits i am trying to use it for a small school to control biosecurity in children
# importar las librerias
import cv2
import mediapipe as mp
import os
import pyttsx3
engine = pyttsx3.init()
engine.setProperty("rate", 130)
engine.setProperty("voice", "spanish latin")
# importar nomnbre de las carpetas
direccion = "C:/Users/valme/OneDrive/protocolo de escuelas/proyectos python/same/proyecto same/fotosP"
#direccion = "C:/Users/valme/OneDrive/protocolo de escuelas/proyectos python/same/deteccion de rostro y cubre bocas/fotos"
etiquetas = os.listdir(direccion)
print("Nombres", etiquetas)
# Llamas el modelo emtrenado
modelo = cv2.face.LBPHFaceRecognizer_create()
# ...............Declaracion del detector
detector=mp.solutions.face_detection # detector
dibujo=mp.solutions.drawing_utils # dibujo
# leer el modelo
modelo.read("modelP.xml")
# ...............realizamos la videocaptura
cap = cv2.VideoCapture(0)
# ...............Inicializamos los parametros de deteccion
with detector.FaceDetection(min_detection_confidence=0.75) as rostros:
while True:
# lectura de videocaptura
ret, frame = cap.read()
# eliminar el error de espejo
frame = cv2.flip(frame, 1)
copia = frame.copy()
# eliminar el error de color
rgb = cv2.cvtColor(copia, cv2.COLOR_BGR2RGB)
crgb = rgb.copy()
# deteccion de rostros
resultado = rostros.process(crgb)
# filtros de seguridad
if resultado.detections is not None:
for rostro in resultado.detections:
#dibujo.draw_detection(frame, rostro)
# print(rostro)
# extraemos el ancho y el alto de nuestra ventanas
al, an, _=frame.shape
# extrtaer xini, yini ancho y alto
xi=rostro.location_data.relative_bounding_box.xmin
yi=rostro.location_data.relative_bounding_box.ymin
ancho=rostro.location_data.relative_bounding_box.width
alto=rostro.location_data.relative_bounding_box.height
# conversion a pixeles
xi=int (xi * an)
yi=int (yi * al)
ancho=int (ancho * an)
alto=int (alto * al)
xf=xi + ancho
yf=yi + alto
# extraccion de pixeles cara
cara=crgb[yi:yf, xi:xf]
# redimensionar las fotos
cara=cv2.resize (cara, (150, 200), interpolation=cv2.INTER_CUBIC)
cara=cv2.cvtColor (cara, cv2.COLOR_BGR2GRAY)
caraP = cara.copy()
# extraemos el ancho y el alto de nuestra ventanas
al, an, _ = copia.shape
# extrtaer xini, yini ancho y alto
xi = rostro.location_data.relative_bounding_box.xmin
yi = rostro.location_data.relative_bounding_box.ymin
ancho = rostro.location_data.relative_bounding_box.width
alto = rostro.location_data.relative_bounding_box.height
# conversion a pixeles
xi = int(xi * an)
yi = int(yi * al)
ancho = int(ancho * an)
alto = int(alto * al)
xf = xi + ancho
yf = yi + alto
# realizar la prediccion
prediccion = modelo.predict(caraP)
t= 37
o=92
#mostrar resultado
print(prediccion)
print(etiquetas)
cv2.putText(copia, "".format(etiquetas[0]), (xi, yf+15), 1, 1.3, (20,100,255), 1, cv2.LINE_AA)
cv2.putText(copia, "t={} ,O={}% ".format(t,o), (xi, yf + 40), 1, 1.3, (0, 0, 255), 1,
cv2.LINE_AA)
cv2.rectangle(copia, (xi, yi), (xf, yf), (0,0,255), 2)
#print(copia)
# mostramos los fotogramas
cv2.imshow("Reconocimiento Facial y CubreBocas", copia)
# leyendo una tecla
t = cv2.waitKey(1)
if t == 27 :
break
# engine.say("Listo Listo Listo fotos tomadas {} ahora colocate el cubreboca , presione [S] para continuar".format(etiquetas))
#engine.runAndWait()
#conti = input("¿Listo fotos tomadas {} ahora colocate el cubreboca , presione [S] para continuar")
cap.release()
cv2.destroyAllWindows()