尝试检测图像时出现NameError

时间:2019-02-07 05:39:28

标签: python image face-recognition

我创建了2个文件,第一个调用train.py,第二个faces.py我尝试通过训练数据来开发人脸识别和识别。但是当我运行它时失败了。我为两个文件都附加了代码。我帮助某人可以就此事为我提供帮助。我尝试运行faces.py,但是失败了。当我尝试打印(roi_gray)时也显示错误。

import os
import cv2
import numpy as np
from PIL import Image
import pickle

BASE_DIR = os.path.dirname(os.path.abspath(__file__))
image_dir = os.path.join(BASE_DIR, "images22")

face_cascade = 
cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')

current_id = 0
label_ids = {}
y_labels = []
x_train = []

recognizer = cv2.face.LBPHFaceRecognizer_create()
for root, dirs, files in os.walk(image_dir):
    for file in files:
    if file.endswith("png") or file.endswith("jpg"):
        path = os.path.join(root, file)
        label = os.path.basename(os.path.dirname(path)).replace("","-").lower()
        #print(path)
        #print(label, path)
        if not label in label_ids:
            label_ids[label] = current_id
            current_id += 1
        id_ = label_ids[label]
        #print(label_ids)
        #y_labels.append(label)
        #x_train.append(path)

        pil_image = Image.open(path).convert("L")
        image_array = np.array(pil_image, "uint8")
        #print(image_array)
        faces = face_cascade.detectMultiScale(image_array, scaleFactor=1.5, 
        minNeighbors=5)

        for(x,y,w,h) in faces:
            roi = image_array[y:y+h, x:x+w]
            x_train.append(roi)
            y_labels.append(id_)



 #print(y_labels)
 #print(x_train)

with open("labels.pickle",'wb') as f:
    pickle.dump(label_ids, f)

recognizer.train(x_train,np.array(y_labels))
recognizer.save("trainner.yml")

这是faces.py的代码

import numpy as np
import cv2


face_cascade = 
cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainner.yml")


cap = cv2.VideoCapture(0)

while(True):
   # Capture frame-by-frame
   ret, frame = cap.read()
   gray  = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
   faces = face_cascade.detectMultiScale(gray, scaleFactor=1.5, 
   minNeighbors=5)


for (x, y, w, h) in faces:
    #print(x,y,w,h)
    roi_gray = gray[y:y+h, x:x+w] #(ycord_start, ycord_end)
    roi_color = frame[y:y+h, x:x+w]

    id_, conf = recognizer.predict(roi_gray)
    if conf>=4 and conf <=85:




    img_item = "my-image.png"
    cv2.imwrite(img_item, roi_gray)

    color = (255,0,0) #BGR 0-255
    stroke = 2
    end_cord_x = x + w
    end_cord_y = y + h
    cv2.rectangle(frame,(x,y),(end_cord_x,end_cord_y),color,stroke)


    cv2.imshow('frame',frame)
    if cv2.waitKey(20) & 0xFF == ord('q'):
        break




# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()

1 个答案:

答案 0 :(得分:1)

删除此:

print(roi_gray)

或将其移动到此for循环之后:

for (x, y, w, h) in faces:
    #print(x,y,w,h)
    roi_gray = gray[y:y+h, x:x+w] #(ycord_start, ycord_end)
    roi_color = frame[y:y+h, x:x+w]

您正在尝试打印该行上不存在的某些东西,从而引发错误。