Image-based target point position detection method and apparatus, and electronic device
A target point and point position technology, which is applied in the field of image-based target point position detection methods, devices, electronic equipment and storage media, and can solve problems such as low target point position detection performance.
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Embodiment 1
[0027] An image-based target point position detection method disclosed in this embodiment, such as figure 1 As shown, the method includes: Step 110 to Step 130.
[0028] Step 110, acquiring several image samples marked with the position of the real target point.
[0029] Before detecting the position of the target point through the neural network model, it is first necessary to construct a training sample to train the neural network model. In the embodiment of the present application, the detection of the key points of the face is taken as an example to illustrate the specific implementation of the method for detecting the position of the target point based on the image. Therefore, it is necessary to construct the training samples of the neural network model based on the face image. That is, the step of obtaining several image samples marked with real target point positions includes: obtaining several image samples marked with real face key point positions.
[0030] In some ...
Embodiment 2
[0059] An image-based target point position detection device disclosed in the embodiment of the present application, such as Figure 5 As shown, the device includes:
[0060] An image sample acquisition module 510, configured to acquire a number of image samples marked with real target point positions;
[0061] The model training module 520 is used to calculate the loss value of the neural network model according to variables through the loss function of the neural network model, and adjust the parameters of the neural network model with the goal of minimizing the loss value to train the neural network model. Network model; wherein, the loss function is configured to increase monotonically relative to the absolute value of the variable, the gradient function corresponding to the loss function is a monotonically decreasing function and the value of the gradient function is greater than 1 and when the variable approaches When infinity gradually approaches 1; the variable is use...
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