Smoking recognition method, device and equipment for logistics warehouse and storage medium
An identification method and warehouse technology, applied in the field of logistics warehouse management, can solve problems such as fire expansion and spread, difficulty in evacuating people, and goods blocking evacuation channels, etc., and achieve the effects of improving output efficiency, facilitating call and training, and reducing image processing time
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0052] Please see figure 1 , the present embodiment provides a smoking recognition method for a logistics warehouse, including:
[0053] Step S1: Obtain the historical images of smoking behavior, mark the historical images with targets, and establish an image data set; the targets include cigarette butts, fingers with cigarettes and smoke;
[0054] Step S2: Create a YOLOv4 model, add hole convolution to the BackBone network in the YOLOv4 model, and obtain an improved YOLOv4 model;
[0055] Step S3: Input the image data set in step S1 into the improved YOLOv4 model for training to obtain a smoking recognition model;
[0056] Step S4: Input the image of the logistics warehouse into the smoking recognition model, and judge whether there is smoking behavior in the image.
[0057] Specifically, in step S1, smoking behaviors in different scenarios are collected, such as gesture smoking, cigarette in mouth, cigarette holder, red dot of cigarette butt, smoke, etc. The images of smo...
Embodiment 2
[0084] The present invention also provides a smoking identification device for logistics warehouses, see Figure 5 , the device consists of:
[0085] The data set creation module is used to obtain historical images of smoking behavior, carry out target labeling to historical images, and establish an image data set; the target includes cigarette butts, fingers with cigarettes and smoke;
[0086] The model creation module is used to create the YOLOv4 model, and the hole convolution is added to the BackBone network in the YOLOv4 model to obtain an improved YOLOv4 model;
[0087] The model training module is used to input the image data set in the data set creation module into the improved YOLOv4 model for training to obtain a smoking recognition model;
[0088] The smoking recognition module is used for inputting the image of the logistics warehouse into the smoking recognition model, and judging whether there is smoking behavior in the image.
[0089] Wherein, the data set cre...
Embodiment 3
[0092] The above-mentioned embodiment 2 describes in detail the smoking recognition device for logistics warehouses of the present invention from the perspective of modular functional entities. The smoking recognition device for logistics warehouses of the present invention is described in detail below from the perspective of hardware processing.
[0093] Please see Image 6 The smoking recognition device 500 for logistics warehouses may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (for example, one or more processors) and Storage 520, one or more storage media 530 (such as one or more mass storage devices) for storing application programs 533 or data 532 . Wherein, the memory 520 and the storage medium 530 may be temporary storage or persistent storage. The program stored in the storage medium 530 may include one or more modules (not shown in the figure), and each...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com