CoinShift Imaging Box 📦📦

CoinShift Imaging Box: A collection of efficient and faster implementation of SOTA Object Detection and Segementation Models.

Why CoinShift Imaging?

Want to get Started with Advanced Computer Vision and NLP?
- Coinshift Provides you a large variety of Computer Vision and NLP Pipelines.
Want to run high end latest Sate of the Art Models, but lack of GPU and RAM?
- All implementation in CoinShift is done using Google Collab or Kaggle Kernals

Some key Features!!

* Run Training and Inference in one place.
* All implementation of NLP Task are done by using Hugging Face.
* Train your model over custome data very easily.

Who Can Use CoinShift Imaging Box?

🚩 CoinShift Imaging Box Templates are meant for those people who have a Intermidiate Knowledge over Object Detection and Segementation models and Algorithms.

🚩 CoinShift Only Provide you a Basic Template to Kick Start your intial part on any Detection or Segementation or Gans or NLP Project or Task, But you still need to add some custom cfg and other file according to your datasets or corpus.

Important Elements

A) Inference Engine
- Original pretrained models (from original authors and implementations) for inferencing and analysing
- Pretrained models on coco, voc, cityscpaes, type datasets
- Useful to analyse which algorithm works best for you
- Useful to generate semi-accurate annotations (coco, pascal-voc, yolo formats) on a new dataset

Create real-world Object Detection applications

Wheat detection in field	Multi-Human Pose Detection	Ship Detection in Oceans on Satellite Images

Underwater Fish Detection	Real-Time Object Detection on Crowd	Real world Object Detection using Facebook DETR

Car Detection using YoloV5	Object Detection using RetinaNET	Human Pose Detection using HRNET

Mask Detection using CNN	Tiger Detection in wild using Yolov5