opencv object detection

The author of this article is Pedro F. felzenszwalb wait a minute, famous DPM in the target detection model. The work of this article is a cascade of DPM (deformed component models) to speed up detection.The accelerated way, now followed by the calculation of certain parts of the score, assumes that the values are less than a certain threshold value, discarding the position of the object to continue to dete

Reference URL: github:https://github.com/naisy/realtime_object_detection2018.10.16SSD Object Detection Summary:Remember to take a cursory look at the notes and start training the modelError: 1, with branch1.5,tensorflow-gpu==1.8 training model in GT730, video memory 2g, can not run, tensorflow-gpu==1.5 no NoMaxSuppressionv3,2, using the pre-training model ssd_mobilenet_coco_2018_1_28,tensorflowgpu==1.5 trai

A problem was encountered in the recent project where the Window object was rendered when the page was loaded, an object obj was added to the window during rendering, a file was loaded, and an attribute para was added to obj, but the process was asynchronous.You then need to detect if the window has an Obj object, and if the Obj

and the samples on the margin are not counted as E or H. The whole is to continuously optimize SVM by selecting the samples that are difficult to distinguish, the difference between common SVM and lsvm is that the sample selection method is the same for different loss functions. The sample selection process is as follows, Let C1 d be an initial cache of examples.Algorithm repeatedly trains a model and updatesCache as follows:1) Let T: = (CT) (train a model using CT ).2) if h (T; d) CT stop and

Haven't written a blog for a long time. In fact, there is nothing to write yourself ... The level is limited, eh .... The robot has recently been engaged in kinematics, so the depth vision is neglected here. However, recently saw a previous article feel very interesting, so want to take out and share with you. The title of the article is titled "Sliding Shapes for 3D object detection in Depth Images", whi

unlike rcnn each candidate area to the depth of the network feature, but the entire map to mention a feature, and then map the candidate frame to the CONV5, Because the size of the candidate box is different, the mapping to the CONV5 is still different, so the SPP layer will need to be extracted to the same dimension of the characteristics, and then classification and regression, the following ideas and methods are consistent with RCNN. In fact, this is a lot faster than the original, because b

Detection of the existence of attributes in an object can be judged by several methods. 1. Use in keywordThis method can be used to determine whether an object's own properties and inherited properties exist. Copy Code code as follows: var o={x:1}; "X" in O; True, own property exists "Y" in O; False "ToString" in O; True, is an inherited property 2. Use the hasOwnProperty ()

Using unityengine;using System.collections;public class Move:monobehaviour {gameobject go;//use this for initialization void Start () {go= gameobject.find ("C4"); Cubego.renderer.material.color = color.red named C4; Set its material to red}//update is called once per framevoid update () {//To detect in real time in each frame whether the keyboard is pressed and to control the direction of C4 movement via W, S, A, D keys if (Input.getkey (K EYCODE.W)) {go.transform.Translate (

Object Contour Detection with a fully convolutional encoder-decoder network Using convolutional encoding and decoding network to detect the edges of primary targets The network structure is:Code: VGG-16Decoding: Reverse pooling-convolution-activation-dropout Convolution cores: The number of channels of every decoder layer is properlyDesigned to allow unpooling the maxpooling layer from its corresponding.