Image feature data extraction method, system and related device

A technology of image features and extraction methods, applied in the field of data processing, can solve problems such as inability to fully release DDR reading and writing capabilities, unsuitable expansion, and wiring congestion, so as to achieve uninterrupted data output of the pipeline, reduce data reading pressure, and meet input requirements. effect of demand

CN113706366APending Publication Date: 2021-11-26LANGCHAO ELECTRONIC INFORMATION IND CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2021-11-26

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Abstract

The invention provides an image feature data extraction method, which comprises the following steps: acquiring image feature data, and determining a corresponding parallel channel number; taking the number of parallel channels as the depth of the image feature data, and increasing the height of the image feature data; using a preset number of RAMs of the FPGA as first-level caches of the DDR for data multiplexing; and configuring a register corresponding to the convolution kernel at the rear end of the first-stage cache, and outputting the image feature data line by line by utilizing the register. According to the invention, the read-write efficiency of the DDR can be improved to the maximum extent, uninterrupted data output of the assembly line is realized, meanwhile, the data reading pressure of the DDR is reduced, and the input requirement of a rear-end high-bandwidth convolution calculation unit can be met. The invention also provides an image feature data extraction system, a computer readable storage medium and electronic equipment, which have the above beneficial effects.
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Description

technical field

[0001] The present application relates to the field of data processing, in particular to a method, system and related devices for extracting image feature data. Background technique

[0002] Currently, CNN (Convolutional Neural Networks, Convolutional Neural Networks) convolutional data extraction process mainly has the following two implementation methods:

[0003] 1. Cache the image feature data into the off-chip DDR (Dynamic Random Access Memory, Dynamic Random Access Memory) of FPGA (Field-Programmable Gate Array, and read only 3*3 data each time for volume By using multiple reads of small-scale DDR, the pressure on FPGA storage resources is reduced, the difficulty of wiring is reduced, and the rate of convolution multiplication of the back-end pipeline is improved.

[0004] Because 3*3 data is equivalent to three 3*1 data, to read a 3*3 data, you need to send 3 read and refresh commands to the DDR, and the address needs to jump, and the small data read ...

Examples

Embodiment Construction

[0044] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0045] The three-dimensional convolution calculation process performed in the CNN network is as follows: see figure 1 , figure 1 For the schematic diagram of the three-dimensional convolution calculation process provided in this application, it is assumed that a color image is 6×6×3, where 3 refers to three color channels, which can be used as a stac...