Ubuntu-Deep-Learning-Environment-Setup
TensorFlow-object-detection-tutorial
| Ubuntu-Deep-Learning-Environment-Setup | TensorFlow-object-detection-tutorial | |
|---|---|---|
| - | 1 | |
| 49 | 150 | |
| - | - | |
| 3.9 | 0.0 | |
| over 3 years ago | almost 4 years ago | |
| Python | ||
| - | - |
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.
Ubuntu-Deep-Learning-Environment-Setup
We haven't tracked posts mentioning Ubuntu-Deep-Learning-Environment-Setup yet.
Tracking mentions began in Dec 2020.
TensorFlow-object-detection-tutorial
-
Python CUDA - Multiprocessing/Pipes/Queues
I am trying to accomplish something similar to this with yolo5. https://github.com/pythonlessons/TensorFlow-object-detection-tutorial
What are some alternatives?
AnimeGANv2 - [Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime
ImageAI - A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
NvidiaRTX-LHRv2Unlocker - The first fully automated BIOS modifier for RTX cards with LHR v2 lock.
cupy - NumPy & SciPy for GPU
gaussian_splatting_notes - A detailed formulae explanation on gaussian splatting
pdf2image - A python module that wraps the pdftoppm utility to convert PDF to PIL Image object
PINTO_model_zoo - A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
pytorch2keras - PyTorch to Keras model convertor
a-PyTorch-Tutorial-to-Object-Detection - SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
viseron - Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.