Search Results for "testing"
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Showing 9 open source projects for "testing"
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GoogleTest
Google Testing and Mocking Framework
GoogleTest is Google's C++ mocking and test framework. It's used by many internal projects at Google, as well as a number of notable projects such as The Chromium projects, the OpenCV computer vision library, and the LLVM compiler. This GoogleTest project is actually a union of what used to be two separate projects: the old GoogleTest and GoogleMock, an extension of GoogleTest for writing and using C++ mock classes. Since they were so closely related, they were merged to create an even... -
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OpenNN - Open Neural Networks Library
Machine learning algorithms for advanced analytics
OpenNN is a software library written in C++ for advanced analytics. It implements neural networks, the most successful machine learning method. Some typical applications of OpenNN are business intelligence (customer segmentation, churn prevention…), health care (early diagnosis, microarray analysis…) and engineering (performance optimization, predictive maitenance…). OpenNN does not deal with computer vision or natural language processing. The main advantage of OpenNN is its... -
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Tiny
Tiny Face Detector, CVPR 2017
...The method is designed to detect tiny faces (i.e. very small-scale faces) by combining multi-scale context modeling, foveal descriptors, and scale enumeration strategies. It provides training/testing scripts, a demo (tiny_face_detector.m), model loading, evaluation on WIDER FACE, and supporting utilities (e.g. cnn_widerface_eval.m). The code depends on MatConvNet, which must be compiled (with GPU / CUDA / cuDNN support) for full performance. Pretrained model provided (ResNet101-based, plus alternatives). Demo and evaluation scripts for benchmark datasets. ... -
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OpenCE
Contrast Enhancement Techniques for low-light images
...OpenCE leverages a feature pyramid structure combined with a refinement stage to improve keypoint detection accuracy across multiple scales, particularly for challenging poses in crowded scenes. The repository includes training scripts, pretrained models, and testing code, allowing users to reproduce results reported in the paper. It supports standard human pose estimation benchmarks such as COCO, with configurations optimized for accuracy and efficiency. As an open resource, OpenCE offers researchers and practitioners a strong baseline for pose estimation and a foundation for extending CPN-based methods. -
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IGVC IITK Data
Data useful for testing autonomous navigation algorithms
This repository is only used for the purpose of dataset storage for Team IGVC, IITK. For the relevant code, see our GitHub repositories. (https://github.com/igvc-iitk). The recorded data is used for testing various algorithms related to Computer Vision, SLAM, Motion Planning etc. -
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Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono. -
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HashingBaselineForImageRetrieval
Various hashing methods for image retrieval and serves as the baseline
This repository provides baseline implementations of deep supervised hashing methods for image retrieval tasks using PyTorch. It includes clean, minimal code for several hashing algorithms designed to map images into compact binary codes while preserving similarity in feature space, enabling fast and scalable retrieval from large image datasets. -
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cvworkbench
Computer vision workbench
Its main purpose is to help with the computer vision software design, developement and testing. By using a graphical diagram editor that defines analysis flow, different algorithm combinations can be tried, with different parameters, very quickly and with no coding. -
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Levo
Application to annotate objects and events in videos and pictures.
This software allows to label events in videos (e.g. phoning, hand-shaking,...) and objects in images (e.g. person, car,...). The annotation of events and objects are saved into XML files and can be used for training and/or testing computer vision algorithms. In particular, LEVO can visualize and write PASCAL VOC-compatible annotation files. Some annotations from LABEL ME can be read as well. It has been tested on MS Windows. However, since it is Java-based code, it should works on Unix-like systems as well. VLC player is required to handle videos. -
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