Author: Deep Learner

Deep Learning

A Deep Learning library for Model Building, Interpretability & Deployment

chitra chitra (चित्र) is a Deep Learning library for Model Building, Explainable AI, Data Visualization, API Building & Deployment. Load Image from Internet url, filepath or numpy array and plot Bounding Boxes on the images easily. Model Training and Explainable AI. Easily create UI for Machine Learning models or Rest API backend that can be deployed for serving ML Models in Production. 📌 Highlights: [New] Framework Agnostic Model Serving & Interactive UI prototype app ✨🌟 [New] Data Visualization, Bounding Box […]

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RESTful API

RESTful API for encoding/decoding messages into/from images

ImageSecrets RESTful API for encoding/decoding messages into/from images. Tech/framework used Python 3.9 FastAPI PostgreSQL with Tortoise ORM Docker Heroku Features Image steganography to encode and decode messages User management and authentication Great documentation via OpenAPI What I’ve learned Python – Improved knowledge of testing, asynchronous development, ORMs, coverage FastAPI – Gained great experience with the framework NumPy – Used for reading and editing image pixel data Databases – Learned how to use SQLAlchemy and Tortoise ORM for asynchronous database development […]

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ORM

A fast, user friendly ORM and query builder which supports asyncio

Piccolo A fast, user friendly ORM and query builder which supports asyncio. Read the docs. Features Some of it’s stand out features are: Support for sync and async. A builtin playground, which makes learning a breeze. Tab completion support – works great with iPython and VSCode. Batteries included – a User model, authentication, migrations, an admin GUI, and more. Modern Python – fully type annotated. Syntax The syntax is clean and expressive. You can use it as a query builder: […]

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Python

Using the Python return Statement Effectively

The Python return statement is a key component of functions and methods. You can use the return statement to make your functions send Python objects back to the caller code. These objects are known as the function’s return value. You can use them to perform further computation in your programs. Using the return statement effectively is a core skill if you want to code custom functions that are Pythonic and robust. In this course, you’ll learn: How to use the […]

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Command-line Tools

Color text streams with a polished command line interface in python

colout(1) — Color Up Arbitrary Command Output Synopsis colout [-h] [-r RESOURCE] colout [-g] [-c] [-l min,max] [-a] [-t] [-T DIR] [-P DIR] [-d COLORMAP] [-s] [-e CHAR] [-E CHAR] [–debug] PATTERN [COLOR(S) [STYLE(S)]] Description colout read lines of text stream on the standard input and output charactersmatching a given regular expression PATTERN in given COLOR and STYLE. If groups are specified in the regular expression pattern, only them are takeninto account, else the whole matching pattern is colored. You […]

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Tracker

3D Object Detection and Tracking using center points in the bird-eye view

CenterPoint 3D Object Detection and Tracking using center points in the bird-eye view. Center-based 3D Object Detection and Tracking,Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl,arXiv technical report (arXiv 2006.11275) @article{yin2021center, title={Center-based 3D Object Detection and Tracking}, author={Yin, Tianwei and Zhou, Xingyi and Kr{“a}henb{“u}hl, Philipp}, journal={CVPR}, year={2021}, } This repo is an reimplementation of CenterPoint on the KITTI dataset. For nuScenes and Waymo, please refer to the original repo. Please refer to INSTALL.md for installation. We provide two configs, centerpoint.yaml for the […]

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Deep Learning

Low-Light Image and Video Enhancement Using Deep Learning

Lighting-the-Darkness-in-the-Deep-Learning-Era-Open This repository provides a unified online platform, LoLi-Platform http://mc.nankai.edu.cn/ll/, that covers many popular deep learning-based LLIE methods, of which the results can be produced through a user-friendly web interface, contains a low-light image and video dataset, LoLi-Phone https://drive.google.com/file/d/1QS4FgT5aTQNYy-eHZ_A89rLoZgx_iysR/view?usp=sharing, in which the images and videos are taken by various phones’ cameras under diverse illumination conditions and scenes, and collects deep learning-based low-light image and video enhancement methods, datasets, and evaluation metrics. More content and details can be found in our […]

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Filter

PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking

PoseRBPF PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking Citing PoseRBPF If you find the PoseRBPF code useful, please consider citing: @inproceedings{deng2019pose, author = {Xinke Deng and Arsalan Mousavian and Yu Xiang and Fei Xia and Timothy Bretl and Dieter Fox}, title = {PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking}, booktitle = {Robotics: Science and Systems (RSS)}, year = {2019} } @inproceedings{deng2020self, author = {Xinke Deng and Yu Xiang and Arsalan Mousavian and Clemens Eppner […]

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Logging

Simple straight logging your Python code

Alog Your goto Python logging without panic on context swtich. Warning: No more logger = logging.getLogger(__name__) in your every file. >>> import alog >>> alog.info(“Hi.”) 2016-12-18 20:44:30 INFO Hi. >>> def test(): … alog.info(“Test 1”) … alog.error(“Test 2”) … >>> test() 2016-12-18 20:45:19 INFO Test 1 2016-12-18 20:45:19 ERROR Test 2 >>> alog.set_level(“ERROR”) >>> test() 2016-12-18 20:45:41 ERROR Test 2 If you’re new to logging, see Why should you use logging instead of print. Installation pip install alog Features Instant […]

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Simulation

A library of functions to compute climate indices from observations or model simulation

xclim: Climate indices computations xclim is a library of functions to compute climate indices from observations or model simulations. It is built using xarray and can benefit from the parallelization handling provided by dask. Its objective is to make it as simple as possible for users to compute indices from large climate datasets and for scientists to write new indices with very little boilerplate. For example, the following would compute monthly mean temperature from daily mean temperature: import xclim import […]

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