Search Results for "utilities"
Sort By:
Showing 13 open source projects for "utilities"
View related business solutions-
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
-
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
1
SAHI
A lightweight vision library for performing large object detection
...However, detection of small objects and inference on large images are still major issues in practical usage. Here comes the SAHI to help developers overcome these real-world problems with many vision utilities. Detection of small objects and objects far away in the scene is a major challenge in surveillance applications. Such objects are represented by small number of pixels in the image and lack sufficient details, making them difficult to detect using conventional detectors. In this work, an open-source framework called Slicing Aided Hyper Inference (SAHI) is proposed that provides a generic slicing aided inference and fine-tuning pipeline for small object detection. -
2
VGGT
[CVPR 2025 Best Paper Award] VGGT
...The repo provides inference pipelines to estimate geometry from monocular inputs, stereo pairs, or brief sequences, together with evaluation harnesses for common geometry benchmarks. Training utilities highlight data curation and augmentations that preserve geometric cues while improving generalization across scenes and cameras. -
3
Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
4
MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers. ... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
5
MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
...The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. MetaCLIP is especially suited for real-world settings where a model must continuously incorporate new visual categories or domains over time. -
6
Detectron
FAIR's research platform for object detection research
...It includes training and evaluation pipelines that handle multi-GPU setups, standard datasets, and common augmentations, which helped standardize experimental practice in detection research. Visualization utilities and diagnostic scripts make it straightforward to inspect predictions, proposals, and losses while training. Although the project has since been superseded by Detectron2, the original Detectron remains a historically important, reproducible reference that still informs many productions. -
7
CoTracker
CoTracker is a model for tracking any point (pixel) on a video
CoTracker is a learning-based point tracking system that jointly follows many user-specified points across a video, rather than tracking each point independently. By reasoning about all tracks together, it can maintain temporal consistency, handle mutual occlusions, and reduce identity swaps when trajectories cross. The model takes sparse point queries on one frame and predicts their sub-pixel locations and a visibility score for every subsequent frame, producing long, coherent trajectories.... -
8
PIFuHD
High-Resolution 3D Human Digitization from A Single Image
...The repo includes training pipelines, dataset loaders (for Multi-POP, etc.), and inference scripts for mesh output including depth maps for postprocessing. To help practical use, there are utilities for normal estimation, texture back-projection, mesh cleanup, and integration with rendering pipelines. -
9
Computer Vision
Best Practices, code samples, and documentation for Computer Vision
In recent years, we've see an extra-ordinary growth in Computer Vision, with applications in face recognition, image understanding, search, drones, mapping, semi-autonomous and autonomous vehicles. A key part to many of these applications are visual recognition tasks such as image classification, object detection and image similarity. This repository provides examples and best practice guidelines for building computer vision systems. The goal of this repository is to build a comprehensive... -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
10
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. Use of “foveal descriptors” to incorporate context for low-resolution faces. ... -
11
Toolbox
Piotr's Image & Video Matlab Toolbox
Piotr’s Image & Video MATLAB Toolbox is a general-purpose MATLAB toolbox for image and video processing and vision tasks, offering utilities, filters, detection, feature extraction, and algorithm building blocks. Example and demo scripts for usage (e.g. acfReadme, detector readmes). It augments MATLAB’s native capabilities (not replacing the Image Processing Toolbox) by providing efficient, reusable wrappers and optimized routines. Example and demo scripts for usage (e.g. acfReadme, detector readmes). ... -
12
Edges
Structured Edge Detection Toolbox
Structured Edge Detection (Edges) is a MATLAB toolbox implementing the structured forests method for fast and accurate edge detection (up to ~60 fps in many settings). The toolbox also includes the Edge Boxes object proposal method, fast superpixel generation, and utilities for training, evaluation, and integration with vision pipelines. High performance (frames per second performance depending on settings). Integration with MATLAB and compatibility with external vision pipelines. Fast edge detection using structured forests (predict structured edge maps). -
13
This Java native library wraps OpenCV (Computer Vision Lib.) function cvMatchTemplate and implements methods for utilities result visualization. It allows efficient images template matching using Normalized Cross-Correlation (NCC) and others algorithms.
- Previous
- You're on page 1
- Next
