csie-lab-aug2021 Goto Github PK

notebooks

Machine learning notebooks in different subjects optimized to run in google collaboratory

onnx2keras

Convert ONNX model graph to Keras model format.

opencv_face_stickers

opencv face stickers

openlidar

DIY 3D LiDAR Scanner

openpilot-lane-detection

an end to end lane detection based on openpilot model https://comma.ai/

openpilot-supercombo-model

Usage of comma.ai trained supercombo onnx model.

openpose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

opnet089

openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 100 supported car makes and models.

p5_vehicledetection_unet

p5_VehicleDetection_Unet

python-data-structures-and-algorithms

Personal Jupyter notebooks written while reading through the book "Python Data Structures and Algorithms" by Benjamin Baka.

python-for-algorithms--data-structures--and-interviews

Files for Udemy Course on Algorithms and Data Structures

python-keras-encoder-decoder-unet

A Keras project with similarly sized encoder-decoder and u-net networks applied to identifying cars

quiver

Interactive convnet features visualization for Keras

raspberry-pi-web-simulator

Raspberry Pi web simulator. Demo address:

retina-unet

Retina blood vessel segmentation with a convolutional neural network

rltorcs

A modified version of TORCS for deep reinforcement learning.

segmentation_models

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

self-driving-autonomous-car-using-open-cv-and-python-neural-network-overtaking-raspberry-pi

CodeBase for my main project Self Driving Autonomous Car using Open-CV and Python | Neural Network | Overtaking | Raspberry Pi. Inspired by Wang Zheng, Most of the code i edited from him, Thanks Wang Zheng for our base code.

self-driving-car

Udacity Self-Driving Car Engineer Nanodegree projects.

semantic-segmentation-for-self-driving-cars

Self-driving cars require a deep understanding of their surroundings. To support this, camera frames are used to recognize the road, pedestrians, cars, and sidewalks at a pixel-level accuracy. In this project, we develop a neural network and optimize it to perform semantic segmentation using Unet and Segnets.

semantic-segmentation-for-self-driving-cars-1

Implementation of U-Net Architecture using Keras to perform Semantic Segmentation on the dataset captures via CARLA self-driving car simulator.

semantic-segmentation-of-roads-for-self-driving-cars-using-unet-cnn

semantic_segmentation_u-net

Semantic Segmentation for Self Driving Cars

street-view-image-segmentation

Neural network using U-Net architecture for semantic segmentation of objects in a street view like pedestrians, cars, traffic poles,etc.

studybook

Study E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)

taiwan_cbr_map

Dynamic visualization of Taiwan crude birth rate map in 2019

testpilot

A minimally invasive fork of Comma AI's OpenPilot 0.5 designed for synchronous simulation environments

tibame_project

Tibame專題程式碼

tinkercad_arduino

TinkerCAD Resources for Freshies Orientation 2020

tools-to-design-or-visualize-architecture-of-neural-network

Tools to Design or Visualize Architecture of Neural Network