Abstract: A method and an apparatus for data calculation in a neural network model, and an image processing method and apparatus. The method for data calculation includes: reading weight data shared by a group of data processing of a data processing layer in a neural network model, into a GroupShared variable of a thread group of a graphics processing unit (GPU), dividing input data of the data processing layer based on the number of threads in the thread group, reading, for each group of input data, weight data corresponding to the group of input data for a data processing in the group of data processing from the GroupShared variable, and performing, by each thread in the thread group, the data processing by using a group of read input data and weight data corresponding to the group of input data, to obtain a calculation result corresponding to the group of input data.

Abstract: An image processing method includes: performing mask processing on a first-type object included in an obtained target video frame image to obtain a candidate image; performing inpainting processing on the first-type object in the candidate image to obtain a first inpainting image, and generating an image initial mask template based on an initial blurred region; performing, when a first quantity of initial blurred pixels included in the image initial mask template reaches a first threshold, morphological processing on a blurred region corresponding to the initial blurred pixel to obtain an image target mask template; performing, when a second quantity of intermediate blurred pixels included in the image target mask template reaches a second threshold, inpainting processing on a pixel region corresponding to the intermediate blurred pixel in the first inpainting image, to obtain a second inpainting image; and determining a target inpainting image based on the second inpainting image.

Abstract: A method and an apparatus for data calculation in a neural network model, and an image processing method and apparatus. The method for data calculation includes: reading weight data shared by a group of data processing of a data processing layer in a neural network model, into a GroupShared variable of a thread group of a graphics processing unit (GPU), dividing input data of the data processing layer based on the number of threads in the thread group, reading, for each group of input data, weight data corresponding to the group of input data for a data processing in the group of data processing from the GroupShared variable, and performing, by each thread in the thread group, the data processing by using a group of read input data and weight data corresponding to the group of input data, to obtain a calculation result corresponding to the group of input data.