TrainYourOwnYOLO
taco
| TrainYourOwnYOLO | taco | |
|---|---|---|
| 1 | 2 | |
| 635 | 1,211 | |
| - | 1.3% | |
| 0.0 | 0.0 | |
| over 1 year ago | 21 days ago | |
| Jupyter Notebook | C++ | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TrainYourOwnYOLO
-
help calculating AP for yolov3 on matlab also my recall precision plot looks jank, more info in comments
Hey, so im pretty new to this and used https://github.com/AntonMu/TrainYourOwnYOLO to train a yolov3 model for pedestrian detection. I'm using the kitti object detection dataset.
taco
-
The Distributed Tensor Algebra Compiler (2022)
I agree! Much of this work was done as part of the overarching TACO project (https://github.com/tensor-compiler/taco), in an attempt to distribute sparse tensor computations (https://rohany.github.io/publications/sc2022-spdistal.pdf). MLIR recently (~mid 2022) began implementing the ideas from TACO into a "sparse tensor" dialect, so perhaps some of these ideas could make it into there. I'm working with MLIR these days, and if I could re-do the project now I would probably utilize and targetb the MLIR linalg infrastructure!
- Qué tire la primer piedra, aquien no le ha pasado así....?
What are some alternatives?
SSD-Mobilenet-Custom-Object-Detector-Model-using-Tensorflow-2 - This repository contains the script and process to create custom SSD Mobilenet model for object detection
blitz - Blitz++ Multi-Dimensional Array Library for C++
colabcat - :smiley_cat: Running Hashcat on Google Colab with session backup and restore.
Grassmann.jl - ⟨Grassmann-Clifford-Hodge⟩ multilinear differential geometric algebra
super-resolution - Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
CuTeLib - CUDA Template Library provides simple, typesafe, performant constructs for C++ CUDA projects
tf2patcher - A patcher for TF2 that allows you to apply full-colored decals.
MegEngine - MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架
pix2seq - Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion)
YOLOX - YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
CleanTF2plus - Clean TF2's sequel
theme-ui - Build consistent, themeable React apps based on constraint-based design principles