[OpenR8 solution] HttpServer_DeepLearning_Python (Python TensorFlow Keras deep learning server)
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.
[OpenR8 solution] HttpServer (Web Server)
The function of HttpServer is to transmit the file to be received, and display the content of the received file through the webpage.
[OpenR8 solution] RegressionForest (date analyzing)
Inference results from the use of random forest prediction data.
[OpenR8 solution] Data_Analysis(Date Analyzing)
Data_analysis uses different methods to model learning and inference of data.
[OpenR8 solution] File (File operation, Delete folder, Delete file, Access binary file, Access string and access image)
This article will introduce and demonstrate how to use it, users can integrate functions to the required places according to their needs.
[OpenR8 solution] CGI (The interface program allows your web page to communicate with the www server to achieve interaction with the user)
CGI is a technology for network communication.
[OpenR8 solution] GetComputerID (Get the MAC address)
The computer Media Address Control Address (MAC address) can be obtained automatically by executing the R8 solution.
[OpenR8 solution] Image_MoveMouseThenScreenShot (Mouse control and image screenshot analysis)
This section describes how users can load an existing solution through the R8 software to automatically click on the next image.
[OpenR8 solution] Image_FaceRecognitionCelebrity (Face recognition of famous people)
Using the Caffe framework, the human face in the image is detected and identified through the SSD (Single Shot Multibox detector) method.
[OpenR8 solution] Image_FindBlob (Find objects in the image)
The purpose of this solution is to find objects in the image.
[OpenR8 solution] IntegerList_Caffe_FC (Digital Rule Training with Caffe Full Connection Layer)
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.
[OpenR8 solution] Image_OCR_Caffe_FC (Optical character recognition handwritten numbers using Caffe)
Image_OCR_Caffe_FC is a MNIST handwritten digit number identification using Caffe to identify the number in the image.
[OpenR8 solution] Image_Cap (Detect if the cap is tight)
The Image_Cap is to detect whether the cap is covered and tight.
[OpenR8 solution] Image_GetSharpness (Obtain image sharpness to determine if the image is blurry)
By running the R8 solution, you can automatically obtain the sharpness of the image to determine if the image is blurry.
[OpenR8 solution] Image_FindRotateVerticalAngle (Find the tilt angle of the image object)
Image_FindRotateVerticalAngle is a solution for processing images to find the tilt angle and then rotate the image according to the angle.
[OpenR8 solution] Image_FindBlob2 (Find objects in the image)
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.
[OpenR8 solution] Image_DataAugmentation (Image_DataAugmentation)
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.
[OpenR8 solution] Image_FC2 (control FLIR camera)
The function of Image_FC2 is to get the image captured by the camera, which contains two files.
[OpenR8 solution] Image_Binarize (Image_Binarize)
Image_binarize is used to separate the image from the foreground and background of the scene.
[OpenR8 solution] Image_PCB_FasterRCNN_Keras (Using Keras FasterRCNN for object detection on PCB)
Through the Keras function library, the FASTERRCNN method is used to detect the capacitance above the PCB.