TernausNetV2
ternaus
TernausNetV2: Fully Convolutional Network for Instance Segmentation
OPENAGENTSKILL / DIRECTORY
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ternaus
TernausNetV2: Fully Convolutional Network for Instance Segmentation
underneathall
Python + Inference - Model Deployment library in Python. Simplest model inference server ever.
guojianyang
🔥🔥🔥🔥🔥🔥Docker NVIDIA Docker2 YOLOV5 YOLOX YOLO Deepsort TensorRT ROS Deepstream Jetson Nano TX2 NX for High-performance deployment(高性能部署)
liruiw
Heterogeneous Pre-trained Transformer (HPT) as Scalable Policy Learner.
SwayamInSync
Virtual Clothing Assistant a custom unique implementation of ViTON, allows user to try different clothings virtually
Le0nX
Modern Robotics: Mechanics, Planning, and Control C++ Library --- The primary purpose of the provided software is to be easy to read and educational, reinforcing the con…
rdmtc
Node-RED packaged as Addon for the Homematic CCU3 and RaspberryMatic 🤹♂️
DagnyT
Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor learning loss"
Justin-Tan
TensorFlow Implementation of Generative Adversarial Networks for Extreme Learned Image Compression
zju3dv
Code for "Neural 3D Scene Reconstruction with the Manhattan-world Assumption" CVPR 2022 Oral
georgesung
Implementation of Single Shot MultiBox Detector in TensorFlow, to detect and classify traffic signs
IvanDrokin
This project is dedicated to the implementation and research of Kolmogorov-Arnold convolutional networks. The repository includes implementations of 1D, 2D, and 3D convo…
jeffreydwalter
Python module for interacting with Netgear's Arlo camera system.
Owner-curated external sources. Not filtered by the scores or compatibility controls above; excluded from GitHub rankings and automatic installation.
RedSkill · 流白Livo · 1.0.0
Describe a rain curtain, growing flowering branches or a flock of swallows. This RedSkill package adapts three p5.js templates into sketch.js code with custom colors, density and speed.
Noncommercial use only · Local runtime recording · Use on the source platform