import cv2 import numpy as np import mindspore from mindspore import Tensor, load_checkpoint, load_param_into_net from PIL import Image from main import ResNet, BasicBlock

加载模型

network = ResNet(BasicBlock, [2, 2, 2, 2], num_classes=100) model_path = 'D:/pythonProject7/ckpt/checkpoint_resnet_6-10_25.ckpt' params = load_checkpoint(model_path) load_param_into_net(network, params)

加载标签

with open('label.txt') as f: labels = f.readlines() labels = [l.strip() for l in labels]

加载人脸检测器

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

打开摄像头

cap = cv2.VideoCapture(0)

while True: # 读取视频帧 ret, frame = cap.read()

# 转换通道数
if len(frame.shape) == 2:
    frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2BGR)
elif frame.shape[2] == 4:
    frame = cv2.cvtColor(frame, cv2.COLOR_BGRA2BGR)
if frame.shape[2] == 1:
    frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2BGR)

# 转换为灰度图像
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

# 检测人脸
faces = face_cascade.detectMultiScale(gray, 1.3, 5)

for (x, y, w, h) in faces:
    # 提取人脸图像
    face = frame[y:y + h, x:x + w]
    face = cv2.resize(face, (224, 224))
    if len(face.shape) == 2:
        face = cv2.cvtColor(face, cv2.COLOR_GRAY2BGR)
        face[:, :, 1] = face[:, :, 0]
        face[:, :, 2] = face[:, :, 0]
    elif face.shape[2] == 4:
        face = cv2.cvtColor(face, cv2.COLOR_BGRA2BGR)
    if face.shape[2] == 1:
        face = cv2.cvtColor(face, cv2.COLOR_GRAY2BGR)
    face = cv2.cvtColor(face, cv2.COLOR_BGR2RGB)
    face = face.transpose().astype(np.float32) / 255.
    face = Tensor(face)
    face = face.asnumpy()
    face = np.expand_dims(face, axis=0)
    face = np.transpose(face, (0, 3, 1, 2))
    face = Tensor(face)

    # 预测人脸所属的类别
    output = network(face)
    prediction = np.argmax(output.asnumpy())
    output = Tensor(output)

    # 在图像上标注人脸和类别
    cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
    cv2.putText(frame, labels[prediction], (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)
    
# 显示图像
cv2.imshow('frame',frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
    break

释放摄像头并关闭窗口

cap.release() cv2.destroyAllWindows()