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This is a repository for a Semantic Segmentation inference API using the Gluoncv CV toolkit

The deployment of deep learning model inference on the Java platform includes some common CV and NLP tasks.

The deployment of deep learning model inference on the C++platform includes some common CV and NLP tasks.

Curated tools for the full CV pipeline: training, data augmentation, experiment tracking, inference, edge deployment, and MLOps.

Production ready FastAPI service for deploying computer vision models with classification and detection capabilities

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A flexible framework for orchestrating deep learning models with Ray . It dynamically schedules and serves multiple models — from NLP (e.g., FastText) to CV (e.g., YOLO, SAM) — enabling scalable, distributed, and efficient multi-model inference.

CV-SIP is a real-time computer vision pipeline for stress inference that fuses rPPG-derived physiological signals with facial behavioral markers. It applies classical signal processing and custom fusion logic to produce an interpretable stress index without black-box emotion models.

TF im2txt model for demoing inference on NLP + CV task

Logistic Regression built completely from scratch using NumPy — featuring 4 optimizers, L1/L2/ElasticNet regularization, full statistical inference (p-values, confidence intervals, odds ratios), failure mode analysis, and K-Fold CV across 6 diverse real-world datasets. No sklearn for core implementation.

Code implementation accompanying the paper "Convolutional Vision Transformer for Cosmology Parameter Inference"

Integrate Unity Inference Engine with OpenCV for Unity.

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This repository houses a simple native plugin for the Unity game engine, built in Visual Studio, that leverages the ONNX Runtime to perform inference with computer vision models. The plugin works with models that take a single RGB image.

🧠 Real-time multi-modal inference system fusing EEG, PPG & CV signals for neural state estimation | Made at MIT

Segmentation of road markings using CV techniques and Panoptic Segmentation for inference to detect, trees, roads, cars, poles, etc.

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This repository allows you to training classification models and classification inference API with GluonCV-MXNET and cifar10.

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Test the traning and inference speed of typical deep learning CV algorithms.

This repository contains the Training, Evaluation and Inference of different CV models for Document Visual Query Answering (VQA)

This end-to-end CV pipeline handles local data engineering by sanitizing cat/dog datasets, extracts features via a 3-layer CNN, and provides performance visualizations. It includes a robust inference script compatible with modern formats like .webp.

This project implements a CNN to classify WBCs from microscopic images into 8 different classes. The model is trained using stratified 5-fold CV and a weighted random sampler. It supports single/batch inference. All modules conform to an interface file-based grading/evaluation system.

This is the latest predictive analytics I have done for the summer in 2019. The data set is in total 1.6 GB. I did variable selection and applied random forest with or without cross validation, conditonal inference trees, KNN-CV, and SVM with linear kernel.

Police Computer Programming Search Templates Tracing all avenues pathways traffic videos for calculated clues In the operon similar traits occurrences information gathered by computer to be sorted by techniques of investigation. Coding backwards through to distinguishing mass criteria associated with a person or name and creating a cloud collage of the intricate correct information such as photo web address eye colour biometrics bioinformatics biostatistics cv Resume country of origin passport last port of entry current whereabouts metal detection plastics detection criminal record level of education IQ modus operandi Actus rheas mens rhea relationships associations financial acquisitions advisors attributes attitude emotions mood status acquaintances predeterminations intentions demises So administering criteria associated with a figure in a photograph due to data preserved and deciphered through inference such as height ambulation weight origins clothing shoes bags contents weapons including details of warehousing bills of laden shipping and receiving retail sales theft discounts invoices receipts -all search criteria now associated with mugshots , video evidence headshots The usage of mathematics to portray a likeness to certain criteria a usefulness in direct and indirect financial acquisition and a combined effect to formulate a mindset internal and external TTC robbery suspect( template) as an implication to identity to track Terrorism Suspects{{ Lone Wolves}} Coding backwards through inferences and video evidence to show coexistence of information due to timing locale whereabouts availability intent evidence proof', probability percentage reliability evidence discovery Coding in respect of providing a countermeasure for the implications of a chemical or biological attack. The use of methods of calculating burns intensity affects and how much exposure the added response and calculations of number of people the aspects tat the suspect(s) may be on the run hostage taking type of gas used mustard agent orange chlorine etcetera Determinations to distinguish methods of treatment and involving care of afflicted pain medication and treatment for wounds or swelling rash allergic reaction and trauma The usage of teleportation in determining contents in identifying with the queen in grovers algorithm 4card monte to determine associated with right choice the type of substance. Then with due diligence the systematic repulsion from the body by dissipation dissolving and elimination the neutral residue left from the calculated countermeasure treatments of the afflicted. By identifying a different queen there can be additional treatment allowances through calculated applied mathematics in coding.

C/C++ library for cross-platform inference of computer vision models

A project and blog for the Computer Vision by Deep Learning course 2021 project, group 3.