Bus lane detection method and device based on image recognition and medium

Abstract

The invention relates to artificial intelligence, and discloses a bus lane detection method based on image recognition, the method comprises the following steps: acquiring an original input image of a lane; constructing a feature extraction network, and extracting image features of the original input image, wherein the image features output by the feature extraction network execute operations and convolution operations of a CBL module for multiple times to obtain a feature map of one scale, wherein different intermediate layers of the feature extraction network respectively execute multiple times of CBL module operation, convolution, up-sampling and feature fusion operation to obtain at least three feature maps with different scales; monitoring and identifying the bus lane on the feature maps of the at least four scales by adopting an anchor frame method; and mapping the corresponding bus lane coordinates on the feature map into the coordinates on the original input image, thereby realizing bus lane detection of the original input image. The invention further provides a device, electronic equipment and a computer readable storage medium. According to the invention, the accuracy of bus lane recognition and the recall rate in a difficult scene are improved.

Description

technical field [0001] The present invention relates to artificial intelligence, in particular to a bus lane detection method, device, electronic equipment and computer-readable storage medium based on image recognition. Background technique [0002] With the rapid development of artificial intelligence technology, deep learning is more and more used in computer vision, especially in the field of image recognition. Bus lanes are independent right-of-way lanes specially set up for buses, and are very important infrastructure in urban traffic. Therefore, the detection of bus lanes has become one of the indispensable links in intelligent transportation systems. [0003] Yolo (full name You Only Look Once) is a commonly used deep learning method. It only uses a CNN network to directly predict the category and location of different targets. YOLO solves object detection as a regression problem, based on a separate end-to-end network. Complete the input from the original image to ...

AI Technical Summary

Problems solved by technology

The bus lane detection algorithm based on YOLOv3 can achieve real-time detection and high accuracy in simple scenes such as sunny days, daytime, and clear bus lane lines, but it can achieve real-time detection with high accuracy in haze, rainy days, night, blurred bus lane lines, etc. In difficult scenarios, the accuracy and recall are still relatively low, and there is still a lot of room for improvement

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