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bmn-boundary-matching-network

A pytorch-version implementation codes of paper: "BMN: Boundary-Matching Network for Temporal Action Proposal Generation", which is accepted in ICCV 2019.

car-damage-detective

Assessing car damage with convolution neural networks for a personal auto claims expedition use case

car-damage-detector

Mask R-CNN Model to detect the area of damage on a car. The rationale for such a model is that it can be used by insurance companies for faster processing of claims if users can upload pics and they can assess damage from them. This model can also be used by lenders if they are underwriting a car loan especially for a used car.

craft-pytorch

Official implementation of Character Region Awareness for Text Detection (CRAFT)

cvpr19-face-anti-spoofing

Code for 2nd Place Solution in Face Anti-spoofing Attack Detection Challenge @ CVPR2019

document-image-classification-tl-sg

Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks

fine_tune_mrz

human-falling-detect-tracks

AlphaPose + ST-GCN + SORT.

iagcwd

An improved contrast enhancement method for image. :camera:

irs_tabformer

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

paddleocr

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

pix2struct_jsl

pupil-detection

Detects pupil of the eye from the images/video and create a circle around it.

scanned-document-classification-deep-learning

BFSI sectors deal with lots of unstructured scanned documents which are archived in document management systems for further use.For example in Insurance sector, when a policy goes for underwriting, underwriters attached several raw notes with the policy, Insureds also attach various kind of scanned documents like identity card, bank statement, letters etc. In later parts of the policy life cycle if claims are made on a policy, releted scanned documents also archeived.Now it becomes a tedious job to identify a particular document from this vast repository. The goal of this case study is to develop a deep learning based solution which can automatically classify scanned documents.

spark-nlp

State of the Art Natural Language Processing

spark-nlp-workshop

Public runnable examples of using John Snow Labs' NLP for Apache Spark.

tesseract-preprocessing-convolution-poc

Ipynb POC for Convolutional Preprocessor used to enhance Tesseract's Accuracy

textrecognitiondatagenerator

A synthetic data generator for text recognition

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

unilm

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

wild-ocr

A more complete pipeline to read text in natural scene images (in the wild). It uses multiple Deep Learning methods and sets the emphasis mostly on the preprocessing of text images to improve the performance of the OCR.