Abstract: A face key point detection method includes determining, according to an image containing a face, a multi-channel feature map of the image; converting the multi-channel feature map into a predetermined channel quantity of target feature maps; performing a convolution operation on each target feature map in the predetermined channel quantity of target feature maps by using a convolution kernel corresponding to each target feature map; generating a feature vector corresponding to the image based on a result of the convolution operation on each target feature map; and determining key point coordinates of the face on the image according to the feature vector.

Abstract: A video editing method, apparatus and storage medium are provided. The method includes obtaining an object, the object including one or more images; determining a content element of the object for video editing, the content element having a content type identifier; determining a material set identifier corresponding to the content type identifier according to a first behavior tree logic; determining a video editing material set corresponding to the material set identifier; and obtaining an edited video according to the content element and the video editing material set.

Abstract: A video editing method, apparatus and storage medium are provided. The method includes obtaining an object, the object including one or more images; determining a content element of the object for video editing, the content element having a content type identifier; determining a material set identifier corresponding to the content type identifier according to a first behavior tree logic; determining a video editing material set corresponding to the material set identifier; and obtaining an edited video according to the content element and the video editing material set.

Abstract: A face key point detection method includes determining, according to an image containing a face, a multi-channel feature map of the image; converting the multi-channel feature map into a predetermined channel quantity of target feature maps; performing a convolution operation on each target feature map in the predetermined channel quantity of target feature maps by using a convolution kernel corresponding to each target feature map; generating a feature vector corresponding to the image based on a result of the convolution operation on each target feature map; and determining key point coordinates of the face on the image according to the feature vector.

Abstract: Embodiments of this application provide a neural network model deployment method, a prediction method and a device. The described features can implement deployment of a neural network model to improve the universality of the deployment of the neural network model to the terminal device by obtaining a layer definition and an operation parameter of each network layer of an initial neural network model, executing a target network layer corresponding to the network layers, applying relational connections amongst the target network layers using a net class, converting the operation parameters into a preset format, obtaining a target operation parameter based on the preset format, loading a corresponding target operation parameter in the target network layer, and obtaining a target neural network model based on the target operation parameter.

Abstract: A locking structure and a system using the same are provided. The locking structure includes a rotating unit, a first switch, a sheet and a second switch. The sheet includes a recess and contact to the first switch or the rotating unit. The second switch includes a protrusion movably disposed within the recess.

Abstract: A locking structure and a system using the same are provided. The locking structure includes a rotating unit, a first switch, a sheet and a second switch. The sheet includes a recess and contact to the first switch or the rotating unit. The second switch includes a protrusion movably disposed within the recess.

Abstract: An electrical module and a device using the same are provided. The electrical module comprises a base, a composite component and a pressing sheet. The composite component is disposed on the base and comprises a pad and a conductive sheet. The conductive sheet is embedded in the pad, and the pressing sheet presses on the pad. The pad comprises a main body and a protrusion. The main body has a surface. The protrusion is disposed on the surface of the main body and is compressed between the surface of the main body and the base.

Abstract: An electrical module and a device using the same are provided. The electrical module comprises a base, a composite component and a pressing sheet. The composite component is disposed on the base and comprises a pad and a conductive sheet. The conductive sheet is embedded in the pad, and the pressing sheet presses on the pad. The pad comprises a main body and a protrusion. The main body has a surface. The protrusion is disposed on the surface of the main body and is compressed between the surface of the main body and the base.