After the data source reads the data, we can use various conversion operators to convert one or more DataStreams into new DataStreams. After the data source enters, we can convert the data source into the data format we need according to a series of transformation operators, and then output it. Basic conversion operators (map/ filter/ […]
Tag: transform
UI automation test framework design and PageObject transformation!
During the UI automation testing process, faced with complex business scenarios, we often encounter the following challenges: Simple recording/playback is fast, but cannot adapt to complex scenes; Writing automated test scripts is more flexible, but the workload is heavy and maintainability is poor; The previous encapsulation technology (PageObject) can adapt to various UI scenarios, but […]
TrOCR model fine-tuning [Transformer-based optical character recognition]
The TrOCR (Transformer-based Optical Character Recognition) model is one of the best performing OCR models. In our previous article we analyzed their performance on single lines of printed and handwritten text. However, like any other deep learning model, they have their limitations. TrOCR doesn’t perform well with curved text out of the box. This article […]
Designing IIR digital filter using bilinear transformation method
1. Experimental purpose 1. Be familiar with the principles and methods of designing IIR digital filters using bilinear transformation method. 2. Master the computer simulation method of digital filters. 3. Obtain perceptual knowledge of digital filtering by observing the filtering effect on actual electrocardiogram signals. 2. Experimental content 1. Use bilinear transformation method to design […]
Onnx export swin transformer
1. Configure the swin transformer environment according to the repo. https://github.com/microsoft/Swin-Transformer 2. Create the file export.py in the repo directory. run `python export.py –eval –cfg configs/swin/swin_based_patch4_window7_224.yaml –resume ../weights/swin_tiny_patch4_window7_224.pth –data-path data/ –lock_rank 0` # ———————————————– ———- #SwinTransformer # Copyright (c) 2021 Microsoft # Licensed under The MIT License [see LICENSE for details] # Written by Ze […]
C# Onnx LSTR Transformer-based end-to-end real-time lane line detection
Table of Contents Effect Model information project code download Effect End-to-end real-time lane line detection Model information lstr_360x640.onnx Inputs ———————– name: input_rgb tensor: Float[1, 3, 360, 640] name: input_mask tensor: Float[1, 1, 360, 640] ————————————————– ————- Outputs ———————– name:pred_logits tensor：Float[1, 7, 2] name:pred_curves tensor：Float[1, 7, 8] name:foo_out_1 tensor：Float[1, 7, 2] name:foo_out_2 tensor：Float[1, 7, 8] name:weights […]
AI modeling and training practice based on HF transformers
We often use scikit-learn to model data for both supervised and unsupervised learning tasks. We are familiar with object-oriented design, such as starting a class and calling subfunctions from the class. However, when I personally use PyTorch, I find design patterns that are similar but not the same as scikit-learn. Recommended online tools: Three.js AI […]
Reprint: TransXNet: A new CNN-Transformer visual backbone that aggregates global and local information, with powerful performance!
Article address: https://arxiv.org/abs/2310.19380</code><code>Project address: https://github.com/LMMMEng/TransXNet 00 | Introduction Current situation: Recent research integrates convolutions into transformers to introduce inductive bias and improve generalization performance. (1) The static characteristics of traditional convolution make it unable to dynamically adapt to input changes, resulting in a representation difference between convolution and self-attention, because self-attention dynamically calculates the attention […]
Inverse transformation of time series into images using Gram’s Angle Field (GAF)
In the process of studying “Imaging Time-Series to Improve Classification and Imputation”, I had a question, that is, how to reconstruct the original time series from the obtained Gram sum/difference field (GASF/GADF)? That is, the inverse transformation of time series to image transformation. For the process of converting time series to GASF/GADF, refer to this […]
Osg::Transform/osg::MatrixTransform/osg::PositionAttitudeTransform/osg::autoTransform
One of the most widely used node type families in osg, application examples of osg::autoTransform are as follows: #include <osgUtil/Optimizer> #include <osgDB/ReadFile> #include <osgGA/TrackballManipulator> #include <osgViewer/ViewerEventHandlers> #include <osgViewer/CompositeViewer> #include <osg/Material> #include <osg/Geode> #include <osg/BlendFunc> #include <osg/Depth> #include <osg/Projection> #include <osg/AutoTransform> #include <osg/Geometry> #include <osgDB/WriteFile> #include <osgText/Text> #include <iostream> osg::Node* createLabel(const osg::Vec3 & amp; pos, float […]