Search Results for "mac camera"
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Showing 70 open source projects for "mac camera"
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VGGT-Ω
[CVPR 2026 Oral] VGGT Omega
VGGT-Omega is a Facebook Research computer vision project for feed-forward camera and depth reconstruction. It takes images as input and predicts camera parameters, depth maps, confidence values, and related scene tokens. The project is associated with 3D understanding workflows where models infer scene geometry without a traditional multi-stage reconstruction pipeline. It includes pretrained model variants with different resolutions and text-alignment capabilities, though checkpoint access... -
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Frigate Home Assistant Integration
Frigate integration for Home Assistant
Frigate Home Assistant Integration connects Frigate, an AI-powered network video recorder, with Home Assistant. It allows Home Assistant users to bring Frigate camera entities, object detection events, sensors, and media access into their smart home dashboard. The integration is commonly installed through HACS, but it still requires Home Assistant configuration after installation. It depends on MQTT, because Frigate communicates many of its events and states through that channel. Users can... -
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LLM Vision
Visual intelligence for your home.
LLM Vision is an open-source integration for Home Assistant that adds multimodal large language model capabilities to smart home environments. The project enables Home Assistant to analyze images, video files, and live camera feeds using vision-capable AI models. Instead of relying only on traditional object detection pipelines, it allows users to send prompts about visual content and receive contextual descriptions or answers about what is happening in camera footage. The system can process... -
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HunyuanWorld-Voyager
RGBD video generation model conditioned on camera input
HunyuanWorld-Voyager is a next-generation video diffusion framework developed by Tencent-Hunyuan for generating world-consistent 3D scene videos from a single input image. By leveraging user-defined camera paths, it enables immersive scene exploration and supports controllable video synthesis with high realism. The system jointly produces aligned RGB and depth video sequences, making it directly applicable to 3D reconstruction tasks. At its core, Voyager integrates a world-consistent video... -
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Transparent Background
This is a background removing tool powered by InSPyReNet
This is a background-removing tool powered by InSPyReNet (ACCV 2022). You can easily remove the background from the image or video or bunch of other stuffs when you can make the background transparent! We basically follow the virtual camera settings from pyvirtualcam. If you do not choose to install virtual camera, it will visualize real-time output with cv2.imshow. Use another checkpoint file. Default is trained with composite dataset and will be automatically downloaded if not available. -
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Map-Anything
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Map-Anything is a universal, feed-forward transformer for metric 3D reconstruction that predicts a scene’s geometry and camera parameters directly from visual inputs. Instead of stitching together many task-specific models, it uses a single architecture that supports a wide range of 3D tasks—multi-image structure-from-motion, multi-view stereo, monocular metric depth, registration, depth completion, and more. The model flexibly accepts different input combinations (images, intrinsics, poses,... -
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3D Gaussian Splatting
Original reference implementation of "3D Gaussian Splatting"
Gaussian Splatting is the official implementation of “3D Gaussian Splatting for Real-Time Radiance Field Rendering,” a research project for reconstructing and rendering 3D scenes from collections of images. The system represents scenes as millions of optimized 3D Gaussians rather than traditional meshes or neural fields, allowing high-quality novel view synthesis with real-time rendering performance. It includes training scripts, rendering tools, scene conversion utilities, and viewers for... -
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HunyuanWorld-Mirror
Fast and Universal 3D reconstruction model for versatile tasks
HunyuanWorld-Mirror focuses on fast, universal 3D reconstruction that can ingest varied inputs and produce multiple kinds of 3D outputs. The model accepts combinations of images, camera intrinsics and poses, or even depth cues, then reconstructs consistent 3D geometry suitable for downstream rendering or editing. The pipeline emphasizes both speed and flexibility so creators can go from casual captures to assets without elaborate capture rigs. Outputs can include point clouds, estimated... -
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The Hypersim Dataset
Photorealistic Synthetic Dataset for Holistic Indoor Scene
Hypersim is a large-scale, photorealistic synthetic dataset and tooling suite for indoor scene understanding research. It provides richly annotated renderings—RGB, depth, surface normals, instance and semantic segmentations, and material/lighting metadata—produced from high-fidelity virtual environments. The dataset spans diverse furniture layouts, room types, and camera trajectories, enabling robust training for geometry, segmentation, and SLAM-adjacent tasks. Rendering pipelines and... -
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gopro-dashboard-overlay
Programs to process GoPro MP4 & Generic GPX/FIT files
gopro-dashboard-overlay is a multimedia processing toolkit that generates data-rich overlays on videos using telemetry data from GoPro cameras or external GPS sources. It processes video files alongside GPX or FIT data to render dashboards displaying metrics such as speed, distance, and location directly onto footage. The system supports a wide range of layouts, including maps, gauges, and charts, which can be customized through configuration files. It integrates FFmpeg for rendering and... -
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F1 Race Replay
An interactive Formula 1 race visualisation and data analysis tool
F1 Race Replay is an interactive replay viewer that lets users watch and analyze recorded Formula 1 race sessions with precise control over camera angles, timing, and telemetry overlay, offering a rich experience beyond standard broadcast replays. It ingests official timing and positional data, then renders vehicle movements through track maps and 3D visualizations so fans, analysts, and engineers can review strategy, overtakes, tire degradation effects, and pit stop impacts in detail. Users... -
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Extract TOTP/HOTP secrets
Extract one time password (OTP) secrets from QR codes
The Python script extract_otp_secrets.py extracts one-time password (OTP) secrets from QR codes exported by two-factor authentication (2FA) apps such as "Google Authenticator". -
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Blender GIS
Blender addons to make the bridge between Blender and geographic data
Import in Blender most commons GIS data format, Shapefile vector, raster image, geotiff DEM, OpenStreetMap XML. There are a lot of possibilities to create a 3D terrain from geographic data with BlenderGIS, check the Flowchart to have an overview. Display dynamics web maps inside Blender 3d view, requests for OpenStreetMap data (buildings, roads, etc.), get true elevation data from the NASA SRTM mission. Manage georeferencing information of a scene, compute a terrain mesh by Delaunay... -
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LTX-2.3
Official Python inference and LoRA trainer package
LTX-2.3 is an open-source multimodal artificial intelligence foundation model developed by Lightricks for generating synchronized video and audio from prompts or other inputs. Unlike most earlier video generation systems that only produced silent clips, LTX-2 combines video and audio generation in a unified architecture capable of producing coherent audiovisual scenes. The model uses a diffusion-transformer-based architecture designed to generate high-fidelity visual frames while... -
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ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to... -
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Depth Pro
Sharp Monocular Metric Depth in Less Than a Second
Depth Pro is a foundation model for zero-shot metric monocular depth estimation, producing sharp, high-frequency depth maps with absolute scale from a single image. Unlike many prior approaches, it does not require camera intrinsics or extra metadata, yet still outputs metric depth suitable for downstream 3D tasks. Apple highlights both accuracy and speed: the model can synthesize a ~2.25-megapixel depth map in around 0.3 seconds on a standard GPU, enabling near real-time applications. The... -
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BlenderProc
Blender pipeline for photorealistic training image generation
A procedural Blender pipeline for photorealistic training image generation. BlenderProc has to be run inside the blender python environment, as only there we can access the blender API. Therefore, instead of running your script with the usual python interpreter, the command line interface of BlenderProc has to be used. In general, one run of your script first loads or constructs a 3D scene, then sets some camera poses inside this scene and renders different types of images (RGB, distance,... -
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WorldGen
Generate Any 3D Scene in Seconds
WorldGen is an AI model and library that can generate full 3D scenes in a matter of seconds from either text prompts or reference images. It is designed to create interactive environments suitable for games, simulations, robotics research, and virtual reality, rather than just static 3D assets. The core idea is that you describe a world in natural language and WorldGen produces a navigable 3D scene that you can freely explore in 360 degrees, with loop closure so that the space remains... -
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Frigate
NVR with realtime local object detection for IP cameras
Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. -
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Norfair
Lightweight Python library for adding real-time multi-object tracking
Norfair is a customizable lightweight Python library for real-time multi-object tracking. Using Norfair, you can add tracking capabilities to any detector with just a few lines of code. Any detector expressing its detections as a series of (x, y) coordinates can be used with Norfair. This includes detectors performing tasks such as object or keypoint detection. It can easily be inserted into complex video processing pipelines to add tracking to existing projects. At the same time, it is... -
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The FreeMoCap Project
Free Motion Capture for Everyone
FreeMoCap is an open-source markerless motion capture system that enables users to record human movement using ordinary cameras and convert the footage into usable 3D motion data. The project’s goal is to democratize motion capture by removing the need for expensive suits or proprietary studio hardware, instead relying on computer vision and pose estimation pipelines. It processes synchronized video feeds to reconstruct skeletal motion, which can then be exported for animation, biomechanics... -
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VGGT
[CVPR 2025 Best Paper Award] VGGT
VGGT is a transformer-based framework aimed at unifying classic visual geometry tasks—such as depth estimation, camera pose recovery, point tracking, and correspondence—under a single model. Rather than training separate networks per task, it shares an encoder and leverages geometric heads/decoders to infer structure and motion from images or short clips. The design emphasizes consistent geometric reasoning: outputs from one head (e.g., correspondences or tracks) reinforce others (e.g., pose... -
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SteadyDancer
Harmonized and Coherent Human Image Animation
SteadyDancer is a research-oriented motion stabilization and dancer tracking system designed to analyze and correct motion in videos, making captured performances appear smoother and more stable while preserving expressiveness. It employs computer vision and motion modeling to estimate and reduce unwanted jitters, shakes, or camera wobbles — particularly in dance or movement sequences where traditional smoothing would distort intentional motion. By differentiating between intentional... -
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LingBot-World
Advancing Open-source World Models
LingBot-World is an open-source, high-fidelity world simulator designed to advance the state of world models through video generation. Built on top of Wan2.2, it enables realistic, dynamic environment simulation across diverse styles, including real-world, scientific, and stylized domains. LingBot-World supports long-term temporal consistency, maintaining coherent scenes and interactions over minute-level horizons. With real-time interactivity and sub-second latency at 16 FPS, it is... -
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. CO3Dv2 enables research...
