Deep learning image labeling system and method

Abstract

The invention firstly discloses a deep learning image labeling system. The system comprises an image preprocessing module, an image annotation module and a network training module which are connectedin sequence; the invention further discloses the deep learning image labeling method. The method comprises the following steps that a user uploads video data and performs video frame taking; fuzzy detection and key frame extraction are carried out on the video frame-taking picture to obtain a to-be-labelled picture; part of the to-be-labelled pictures is manually labelled to generate a manual labeling result, and the manual labeling result is used for algorithm training; the trained algorithm is used to perform automatic pre-labeling on the remaining to-be-labelled pictures to generate a pre-labelled result; and a pre-annotation result is rechecked and corrected to generate a final labeling result. The system realizes automatic labeling of image and video data, avoids time and labor wasteof manual labeling, effectively improves the data labeling efficiency, and realizes quick labeling of massive data; Implementation steps are provided for automatic labeling of image and video data, and data labeling workload is greatly reduced.

Description

technical field [0001] The present invention relates to the field of deep learning data labeling, and more specifically, to a deep learning image labeling system and method. Background technique [0002] With the advancement of technology, deep learning neural networks are gradually applied to various industries, especially in the field of image recognition. The neural network is data-oriented, and it needs to train the algorithm on a large amount of labeled data. At present, data labeling is mainly done manually, and there are the following problems: first, the process of manual labeling is time-consuming, labor-intensive, and inefficient; second, it is difficult to complete the task in a short time when faced with massive data; Third, in daily operation and production, most of the generated video data cannot be directly marked. Therefore, users urgently need an image annotation system that can be applied to multiple types of data such as picture data and video data, so a...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a deep learning image labeling system and method to solve the problems of low efficiency of manual labeling, difficulty in completing labeling of massive data in a short time, and direct labeling of video data.

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