Question

我使用keras 2和tf后端和opencv 3，

我希望从网络摄像头中识别图像而不是

test_image = cv2.imread('cat.jpg')"

此外，我还在实时饲料中堆叠打印标签。我只是不知道如何通过循环和识别来连续获取图像。我知道它可以通过opencv VideoCapture完成，只是不知道该怎么做。

我的其他信息是

num_classes = 4

labels[0:202] = 0
labels[202:404] = 1
labels[404:606] = 2
labels[606:] = 3

names = ['cats', 'dogs', 'horses', 'humans']

我希望你们帮助我。提前谢谢。

以下是我从路径

测试图片的示例代码

# Testing a new image
test_image = cv2.imread('cat.jpg')
test_image = cv2.cvtColor(test_image, cv2.COLOR_BGR2GRAY)
test_image = cv2.resize(test_image, (128, 128))
test_image = np.array(test_image)
test_image = test_image.astype('float32')
test_image /= 255
print(test_image.shape)

if num_channel == 1:
    if K.image_dim_ordering() == 'th':
        test_image = np.expand_dims(test_image, axis=0)
        test_image = np.expand_dims(test_image, axis=0)
        print(test_image.shape)
    else:
        test_image = np.expand_dims(test_image, axis=3)
        test_image = np.expand_dims(test_image, axis=0)
        print(test_image.shape)
else:

    if K.image_dim_ordering() == 'th':
        test_image = np.rollaxis(test_image, 2, 0)
        test_image = np.expand_dims(test_image, axis=0)
        print(test_image.shape)
    else:
        test_image = np.expand_dims(test_image, axis=0)
        print(test_image.shape)


# Predicting the test image
print(model.predict(test_image))
print(model.predict_classes(test_image))

Answer 1

如您所言，您可以使用webpack进行网络摄像头输入。流程就是这样

cv2.VideoCapture(0)

如何通过网络摄像头实时识别图像并使用Keras实时显示标签

1 个答案: