Search Results for "metasploitable-2"
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Showing 7 open source projects for "metasploitable-2"
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PairSoft | AP Automation and Doc ManagementStreamline operations and elevate your team's efficiency with PairSoft. Our AP automation, procurement, and document management solutions eliminate manual processes, cut costs, and free your team to focus on strategic initiatives. Experience our state-of-the-art invoice-to-pay solution, now integrated with advanced AI technology for faster, smarter results. Our customers report a significant 70% reduction in approval times and annual savings of $62,000 in employee hours. At PairSoft, we aim to transform your business operations through automation. Explore the future of automation at pairsoft.com, where you can leverage cutting-edge features like invoice capture, OCR, and comprehensive AP automation to transform your workflow. Whether you are a small business or a large enterprise, our solutions are designed to scale with your needs, providing robust functionality and ease of use. Join the growing number of businesses that trust PairSoft.
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DataHub is the leading open-source data catalog helping teams discover, understand, and govern their data assets.Built on an open source foundation with a thriving community of 13,000+ members, DataHub gives you unmatched flexibility to customize and extend without vendor lock-in. DataHub Cloud is a modern metadata platform with REST and GraphQL APIs that optimize performance for complex queries, essential for AI-ready data management and ML lifecycle support.
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SAM 2
The repository provides code for running inference with SAM 2
SAM2 is a next-generation version of the Segment Anything Model (SAM), designed to improve performance, generalization, and efficiency in promptable image segmentation tasks. It retains the core promptable interface—accepting points, boxes, or masks—but incorporates architectural and training enhancements to produce higher-fidelity masks, better boundary adherence, and robustness to complex scenes. The updated model is optimized for faster inference and lower memory use, enabling real-time... -
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MESHROOM
3D reconstruction software
...Photography is the projection of a 3D scene onto a 2D plane, losing depth information. The goal of photogrammetry is to reverse this process. The dense modeling of the scene is the result yielded by chaining two computer vision-based pipelines, “Structure-from-Motion” (SfM) and “Multi View Stereo” (MVS). Fusion of Multi-bracketing LDR images into HDR. Alignment of panorama images. Support for fisheye optics. Automatically estimate fisheye circle or manually edit it. Take advantage of motorized-head file. Easy to integrate in your Renderfarm System. ... -
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fastai
Deep learning library
...These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library. fastai is organized around two main design goals: to be approachable and rapidly productive, while also being deeply hackable and configurable. It is built on top of a hierarchy of lower-level APIs which provide composable building blocks. -
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PIFuHD
High-Resolution 3D Human Digitization from A Single Image
...The method operates by learning an implicit occupancy / surface function conditioned on the image and camera projection; at inference time it queries dense points to reconstruct a mesh via marching cubes. It also uses a two-stage architecture: a coarse global model followed by local refinement patches to capture fine detail, balancing global consistency and local detail. 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. -
The AI coach for teams, built on validated assessments.Give managers and teams proactive, contextual coaching to lead effectively, communicate clearly, and navigate real work situations as they happen.
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5
ChainerCV
ChainerCV: a Library for Deep Learning in Computer Vision
...In ChainerCV, we define the object detection task as a problem of, given an image, bounding box-based localization and categorization of objects. Bounding boxes in an image are represented as a two-dimensional array of shape (R,4), where R is the number of bounding boxes and the second axis corresponds to the coordinates of bounding boxes. ChainerCV supports dataset loaders, which can be used to easily index examples with list-like interfaces. Dataset classes whose names end with BboxDataset contain annotations of where objects locate in an image and which categories they are assigned to. ... -
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ViAmI-Server
Pattern recognition for ADL events
...We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data. -
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Monk Computer Vision
A low code unified framework for computer vision and deep learning
Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection -...
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