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Aarya K H's starred repositories

quickdraw-dataset

Documentation on how to access and use the Quick, Draw! Dataset.

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pdf2htmlEX

Convert PDF to HTML without losing text or format.

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Keras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionnext,lcnet,levit,maxvit,mobilevit,moganet,nat,nfnets,pvt,swin,tinynet,tinyvit,uniformer,volo,vanillanet,yolor,yolov7,yolov8,yolox,gpt2,llama2, alias kecam

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PaddleDetection

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

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mmdetection3d

OpenMMLab's next-generation platform for general 3D object detection.

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LaneDetector

An OpenCV Lane Detector for dummies in C++.

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make-real

Draw a ui and make it real

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neural-tangents

Fast and Easy Infinite Neural Networks in Python

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AutoBots

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artop_examples_learning

Learing Artop examples.

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Arxml-Editor

Similar to Artop editor example. View, add and delete element in arxml.

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mql

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Computer-Vision-

This repository is related to all about Computer Vision - an A-Z guide to the world of Computer Vision. This supplement contains the implementation of algorithms, statistical methods, and techniques (in Python)

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play_with_tensorrt

Sample projects for TensorRT in C++

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SelfTask-GNN

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

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SS-GCNs

[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

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NPTEL-The-Joy-of-Computing-using-Python

Study materials related to this course.

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waymax

A JAX-based simulator for autonomous driving research.

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SSL-Lanes

[CoRL-2022] SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving

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trafficgen

[ICRA 2023] The official code for paper "TrafficGen: Learning to Generate Diverse and Realistic Traffic Scenarios"

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PowerBEV

POWERBEV, a novel and elegant vision-based end-to-end framework that only consists of 2D convolutional layers to perform perception and forecasting of multiple objects in BEVs.

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