The purpose of this solution is to allow users to select images through the web page and obtain a frame of the resulting for object detection.
The function of HttpServer is to transmit the file to be received, and display the content of the received file through the webpage.
Inference results from the use of random forest prediction data.
Data_analysis uses different methods to model learning and inference of data.
This article will introduce and demonstrate how to use it, users can integrate functions to the required places according to their needs.
The computer Media Address Control Address (MAC address) can be obtained automatically by executing the R8 solution.
This section describes how users can load an existing solution through the R8 software to automatically click on the next image.
Using the Caffe framework, the human face in the image is detected and identified through the SSD (Single Shot Multibox detector) method.
The purpose of this solution is to find objects in the image.
This IntegerList_Caffe_FC is a deep learning Caffe framework that uses a multi-layer network to train the model and then test it through the trained model.
Image_OCR_Caffe_FC is a MNIST handwritten digit number identification using Caffe to identify the number in the image.
The Image_Cap is to detect whether the cap is covered and tight.
By running the R8 solution, you can automatically obtain the sharpness of the image to determine if the image is blurry.
Image_FindRotateVerticalAngle is a solution for processing images to find the tilt angle and then rotate the image according to the angle.
Image_FindBlob2 is an example of a solution that frames objects of a specified size and can be used interchangeably with another “Image_FindBlob.doc” file.
Data Augmentation is achieved by modifying the existing images in the dataset to create more images for the machine to learn, thereby expanding the dataset.
The function of Image_FC2 is to get the image captured by the camera, which contains two files.
Image_binarize is used to separate the image from the foreground and background of the scene.
Through the Keras function library, the FASTERRCNN method is used to detect the capacitance above the PCB.
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