Toolbox for Few-Shot Learning
open-exchange is a model conversion and visualization tool to help users inter-operate among different deep learning frameworks. Convert models between PyTorch and Tensorflow.
**Data Description** The detection research of sonar images has a wide range of application value in many fields such as industry, environment and military. Sonar image data is often acquired together with water depth detection and bottom detection data, which enables us to observe the shallow structure of the seabed. This data set was launched by Pengcheng Laboratory, which is currently the largest and most extensive acoustic image data set in the industry. Please contact with firstname.lastname@example.org if you have any questions. ** Download** *Baidu Cloud* https://pan.baidu.com/s/1J1m4jrLPeGdDc5sez75z9A password: 05dg *OneDrive* https://1drv.ms/u/s!AlpdPhejQ4FqiDL25YVhjxxT1WeU?e=DcwBRD **Training Set** The training set contains 4000 forward-looking sonar image files in .bmp format and corresponding annotation result files in .xml format. The file organization structure is as follows: !(/attachments/download/968) The image data in the forward-looking sonar image file represents the acoustic reflection intensity information, and the principle is as follows: !(/attachments/download/969) The pixel with the coordinate !(/attachments/download/978) in the image represents the acoustic reflection intensity information at the direction !(/attachments/download/976) and distance !(/attachments/download/977) in the polar coordinate system. Among them, !(/attachments/download/979) and !(/attachments/download/980) respectively represent the horizontal angle and slant range of the forward looking sonar, !(/attachments/download/981) and !(/attachments/download/982) represent the horizontal and vertical size of the image respectively. The annotation result file contains the detection frame parameters (position and size) and target type of the target in the corresponding sonar image. Target types include cube, ball, cylinder, human body, tyre, circle cage, square cage, and Metal bucket and other 8 categories, the label format is as follows: !(/attachments/download/970) The </sonar> field contains the working parameters of the sonar when the corresponding image is collected, such as the horizontal/vertical angle of the sonar, the range of the sonar slope, and the working frequency of the sonar. **Test Set** Test Set includes A_Board and B_Board, which contains 1000 sonar image in .bmp format and corresponding sonar annotation files in .xml respectively. The sonar parameter information file format is as follows: !(/attachments/download/971) **Extra Information:** The data was collected using Tritech Gemini 1200i forward looking sonar. This data set is the original echo intensity information of the sonar in the form of a two-dimensional matrix, which is stored as a bmp image format for the convenience of process and can be read as 3-channel image data. The data of the 3 channels are equal, so the data of one channel can be used in actual processing; The original sonar image has not been adjusted for gain and is directly displayed as a nearly black image. It is suggested that the display effect of the data after histogram equalization is better, which helps to establish an intuitive understanding of the sonar image, but whether to add gain to the data should not have much influence on the algorithm design (the histogram equalization algorithm can be moved Discussion area for reference) **Data Example** !(/attachments/download/972) The picture above is a forward-looking sonar image. The red box is the target marking frame. From left to right, they are square cage, ball, and tyre. !(/attachments/download/973) The picture above is a forward-looking sonar image. The red box is the target marking frame. From left to right, they are human body, ball, and circle cage. !(/attachments/download/974) The picture above is a forward-looking sonar image. The red box is the target marking frame. From left to right, they are tyre and metal bucket.
Open-source high-performance RISC-V processor
AI模型服务化引擎，用于将AI模型推理程序封装成为Web互联网服务。 目前提供RESTful API、WebSocket和可视化Web GUI等多种形式的互联网API接口服务，支持二进制数据传输和文件上传。
侧扫声呐图像标注软件（Open Side-Scan-Sonar Label Tool），简称**OpenSLT**，是一款能够对XTF格式文件直接进行标注的软件。其工作原理是在线解析XTF格式文件并生成图像，在此基础上进行标注，相比于传统标注方法，该软件能够有效的保留侧扫声呐图像的额外信息，如目标所在帧数、所在采样点、斜距信息等等，方便后续基于深度学习的目标检测算法开发。同时，该软件也支持以YOLO标注格式的输出，具备与传统标注软件相同的功能。