DenseNet Paper Details and PyTorch Replication

DenseNet 1. ResNet and DenseNet ResNet (Deep Residual Network): By establishing a "short-circuit connection" between the front and back layers, this helps to reverse the propagation of gradients during training, resulting in a deeper CNN network. DenseNet: uses a dense join mechanism, where all layers are connected to each other, a ...

Posted on Wed, 01 Dec 2021 05:16:07 -0500 by rsasalm

FPN of Backbone: feature pyramid (pytoch implementation and code analysis)

  Background:          In order to enhance semantics, the traditional object detection model usually only carries out subsequent operations on the last feature map of the deep convolution network, and the down sampling rate (multiple of image reduction) corresponding to this layer is usually large, ...

Posted on Tue, 30 Nov 2021 11:14:55 -0500 by monloi

Image semantic segmentation and object detection

Among the trained image target detection provided by Pytorch, they are R-CNN series networks, and provide easy to call methods for target detection and human key point detection respectively. For the network of target detection, the input images are required to use the same preprocessing method, that is, the pixel value of each image is preproc ...

Posted on Sat, 20 Nov 2021 16:34:29 -0500 by iloveny

Deep learning Yolo algorithm code implementation

preface This blog mainly summarizes the technologies used in Yolo series according to the algorithm code of Yolo series, including anchor box setting, data reading and processing, plug and play attention mechanism module, loss function setting, etc. The code source of this blog is Yolov3 and Yolov4 , the code is based on the tensorflow fra ...

Posted on Thu, 04 Nov 2021 04:51:25 -0400 by taslim

Notes on yoof: you only look one level feature

Reference code: YOLOF 1. General Introduction: review the FPN network commonly used in previous detection networks to fuse features of different scales and detect targets under different scales (targets of different sizes will be assigned to FPN feature maps of different stripes). This is actually a divide and conquer strategy. However, su ...

Posted on Sun, 31 Oct 2021 12:11:41 -0400 by TKKP

2021SC@SDUSC Application and practice of software engineering in school of software, Shandong University -- yoov5 code analysis general.py-4

2021SC@SDUSC preface This is the fourth article of yolov5 code analysis and the last article of general.py. non_max_suppression function def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=None, agnostic=False, multi_label=False, labels=(), max_det=300): """Runs Non-Maximum Suppression ...

Posted on Mon, 25 Oct 2021 06:13:00 -0400 by Clandestinex337

RFBnet paper and its code explanation

RFBnet Before learning, I always looked at CSDN and knowledge, but I still felt that many details were not well understood, so I recently planned to start reading the original text and record my ideas and code analysis. There may be some typos or wrong conclusions. I hope you will forgive me. Abstract The current top target detection netw ...

Posted on Thu, 21 Oct 2021 21:56:08 -0400 by md7dani

Ubuntu 18.04 install and test ROS melody (the difficulty lies in initializing rosdep: sudo rosdep init)

Ubuntu 18.04 install ROS melody and test 1. Update the software source to the domestic stability organization 2. Configure ROS software source sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list' Using echo and command redirection in Linux is a shortcut to write ...

Posted on Fri, 15 Oct 2021 15:23:52 -0400 by dada06

Learn AI from Li Mu - anchor box code analysis - 3

Learn AI from Li Mu - anchor box code analysis - 3 Non maximum suppression prediction bounding box When there are many anchor boxes, many similar prediction bounding boxes with obvious re bands may be output. Around the same target, in order to simplify the output, use non maximum suppression (NMS) to merge similar prediction bounding boxes c ...

Posted on Tue, 12 Oct 2021 16:29:19 -0400 by Nicoza

OpenCV training its own object detection classifier steps

Environment: Python 3.7   OpenCV3.4.3.18 Tools: opencv_annotation.exe opencv_createsamples.exe opencv_traincascade.exe Environment and tools download and installation Terminal command of OpenCV Library under cmd  pip install -i https://pypi.tuna.tsinghua.edu.cn/simple opencv-contrib-python==3.4.3.18 It includes the mai ...

Posted on Thu, 07 Oct 2021 11:12:24 -0400 by Kingskin