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Showing 22 open source projects for "sam"
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SAM 3
Code for running inference and finetuning with SAM 3 model
...Compared with SAM 2, SAM 3 introduces the ability to exhaustively segment all instances of an open-vocabulary concept specified by a short phrase or exemplars, scaling to a vastly larger set of categories than traditional closed-set models. This capability is grounded in a new data engine that automatically annotated over four million unique concepts, producing a massive open-vocabulary segmentation dataset and enabling the model to achieve 75–80% of human performance on the SA-CO benchmark, which itself spans 270K unique concepts. -
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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. -
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SAM 3D Objects
Models for object and human mesh reconstruction
SAM 3D Objects is a foundation model that reconstructs full 3D geometry, texture, and spatial layout of objects and scenes from a single image. Given one RGB image and object masks (for example, from the Segment Anything family), it can generate a textured 3D mesh for each object, including pose and approximate scene layout. The model is specifically designed to be robust in real-world images with clutter, occlusions, small objects, and unusual viewpoints, where many earlier 3D-from-image systems struggle. ... -
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SAM 3D Body
Code for running inference with the SAM 3D Body Model 3DB
SAM 3D Body is a promptable model for single-image full-body 3D human mesh recovery, designed to estimate detailed human pose and shape from just one RGB image. It reconstructs the full body, including feet and hands, using the Momentum Human Rig (MHR), a parametric mesh representation that decouples skeletal structure from surface shape for more accurate and interpretable results. -
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AWS SAM CLI
CLI tool to build, test, debug, and deploy Serverless applications
...With just a few lines per resource, you can define the application you want and model it using YAML. During deployment, SAM transforms and expands the SAM syntax into AWS CloudFormation syntax, enabling you to build serverless applications faster. To get started with building SAM-based applications, use the SAM CLI. SAM CLI provides a Lambda-like execution environment that lets you locally build, test, debug, and deploy AWS serverless applications. -
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AWS Serverless Application Model
An open-source framework for building serverless applications
...To get started with building SAM-based applications, use the AWS SAM CLI. SAM CLI provides a Lambda-like execution environment that lets you locally build, test, and debug applications defined by SAM templates or through the AWS Cloud Development Kit (CDK). You can also use the SAM CLI to deploy your applications to AWS. SAM and SAM CLI are open-sourced under the Apache 2.0 license. -
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segment-geospatial
A Python package for segmenting geospatial data with the SAM
The segment-geospatial package draws its inspiration from segment-anything-eo repository authored by Aliaksandr Hancharenka. To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the segment-anything-py and segment-geospatial Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have adapted the source code of segment-geospatial from the segment-anything-eo repository, and credit for its original version goes to Aliaksandr Hancharenka. -
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Grounded-Segment-Anything
Marrying Grounding DINO with Segment Anything & Stable Diffusion
...The core idea behind the project is to pair Grounding DINO — a zero-shot object detector that can locate objects described by natural language — with Segment Anything Model (SAM), which can produce detailed masks for objects once they are localized. This fusion lets users provide arbitrary text descriptions (e.g., “a cat, a bicycle, or a coffee mug”), have the detection model find relevant bounding boxes, and then use SAM to generate precise segmentation masks that isolate each object in the scene. -
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Lambda Builders
Python library to compile, build & package AWS Lambda functions
Python library to compile, build & package AWS Lambda functions for several runtimes & frameworks. AWS Lambda Builders also supports Custom workflow through a Makefile. Lambda Builders is the brains behind the sam build command from AWS SAM CLI. Lambda Builders is a Python library. It additionally exposes a JSON-RPC 2.0 interface to use in other languages. Build Actions could be implemented in any programming language. Preferably in the language that they are building. Some build actions simply execute a binary (like Golang) without writing a Go script. ... -
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Sa2VA
Official Repo For "Sa2VA: Marrying SAM2 with LLaVA
Sa2VA is a cutting-edge open-source multi-modal large language model (MLLM) developed by ByteDance that unifies dense segmentation, visual understanding, and language-based reasoning across both images and videos. It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about visual content, perform referring segmentation, and maintain temporal consistency across frames in video. With minimal instruction tuning (often one-shot), Sa2VA can handle tasks such as “segment the main subject,” “what are the objects in this scene?”... -
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Mangum
AWS Lambda support for ASGI applications
...Support for binary media types and payload compression in API Gateway using GZip or Brotli. Works with existing deployment and configuration tools, including Serverless Framework and AWS SAM. The heart of Mangum is the adapter class. It is a configurable wrapper that allows any ASGI application (or framework) to run in an AWS Lambda deployment. The adapter accepts a number of keyword arguments to configure settings related to logging, HTTP responses, ASGI lifespan, and API Gateway configuration. -
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SIREN
Renewable Energy Network tool
...The map initially shows the main skeleton of the existing electricity grid infrastructure and current generation stations. The strength of the simulation is in running the SAM models developed by US NREL for each renewable station in your current simulation. SAM calculates a list of power outputs for each hour of the year and shows how they meet the electricity demand and identify generation shortfalls. Weather files created from NASA (MERRA2) satellite data make it applicable worldwide -
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HomeRobot
Mobile manipulation research tools for roboticists
...HomeRobot integrates perception, planning, and control under a unified architecture, supporting AI Habitat for simulation and ROS Noetic for real-world deployment. It provides interfaces for Detic, Grounded-SAM, and Contact-GraspNet, allowing open-vocabulary detection and 3D grasping. -
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crossmap
convert genome coordinates betweeen assemblies
CrossMap is a program for convenient conversion of genome coordinates and genomeannotation files between assemblies (eg. lift from GRCh36/hg18 to GRCh37/hg19 or vice versa).It support file in BAM, SAM, BED, Wiggle, BigWig, GFF, GTF format. -
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PySptools
Hyperspectral algorithms for Python
...New for v0.14.x: a scikit-learn bridge (alpha and partial). The functions and classes are organized by topics: * abundance maps: FCLS, NNLS, UCLS * classification: AbundanceClassification, NormXCorr, KMeans SAM, SID, SVC * detection: ACE, CEM, GLRT, MatchedFilter, OSP * distance: chebychev, NormXCorr, SAM, SID * endmembers extraction: ATGP, FIPPI, NFINDR, PPI * material count: HfcVd, HySime * noise: Savitzky Golay, MNF, whiten * sigproc: bilateral * sklearn: HyperEstimatorCrossVal, HyperSVC and others * spectro: convex hull quotient, features extraction (tetracorder style), USGS06 lib interface * util: load_ENVI_file, load_ENVI_spec_lib, corr, cov and others The library do an extensive use of the numpy numeric library and can achieve good speed. ... -
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converts a SAM file to fasta file. SAM file is a file output from bwa alignment software. It outputs aligned fasta file.
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iMSAT represents a full update of the vcf2MSAT program. This command line python program allows for a user to use the polymorphism data generated using SAM- and BAM-tools and a .fasta alignment file to search for polymorphic microsatellite markers (MSATs or STRs). By identifying polymorphic makers, rather than simple repeat regions as previous programs have done, iMSAT greatly increases the speed at which polymorphic MSATs that can be identified -- saving researchers precious time and money. ...
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pyz80 is a z80 cross-assembler written entirely in Python. It accepts text files with the syntax of the Sam Coupe's popular COMET assembler, and outputs a disk image suitable for loading in SimCoupe or transferring to floppy disk for use with a real Sam.
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HPeak
A HMM-based algorithm for defining enriched regions from ChIP-seq data
...Command (single-end): perl /compbio/software/HPeak3/HPeak.pl -sp HUMAN/MOUSE -format BED -t TREATMENT.inp -c CONTROL.inp -n OUTPUTPREFIX -fmin 100 -fmax 300 -r 36 -ann -wig -seq -interfiles Command (pair-end): perl /compbio/software/HPeak3/HPeak.pl -sp HUMAN/MOUSE -format BED -pe TREATMENT.inp -c CONTROL.inp -n OUTPUTPREFIX -isize 200 -r 100 -pec (if control is PE) -ann -wig -seq –interfiles note: 1. Default species is HUMAN. Also supports MOUSE. Can add any other genome if in need. 2. Default format is BED. Also support ELAND. Will add SAM and BAM. 3. –r specifies read length (this is import through my experience). 4. –pe indicates pair-ended data. 5. If data is pair-ended, -isize refers to insert size (total length of a pair). -
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Python module for the libnet packet construction library (https://github.com/sam-github/libnet). To encourage social coding, the code has been moved to https://github.com/allfro/pylibnet.
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Spike Asset Manager (SAM) is an open-source cross-platform framework for probing a system for components and reporting them. It includes a driver file that probes for components commonly found in a LAMPJ stack (Apache, MySQL, PHP, Tomcat, etc).
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roboteks - robot eksperymentalny. Nie uzywa gotowych odpowiedzi, próbuje analizowac pytanie uzytkownika i sam tworzyc odpowiedz adekwatna do zadanego pytania. przeznaczony dla polskich uzytkownikow
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