Aymane Chilah's repositories
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
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)
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.