object-detection-pipelines

🚀 The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems!

Almost Real-time Object Detection using Apple's CoreML and YOLO v1 -

Open Toolkit for Painless Object Detection

Serve machine learning models using tensorflow serving

🎵 A repository for manually annotating files to create labeled acoustic datasets for machine learning.

Object detector from HOG + Linear SVM framework

Multi-class object detection pipeline—Single Shot MultiBox Detector (SSD) + YOLOv3 (real-time) + focal loss (RetinaNet) + Pascal VOC 2007 dataset

The goal of the project is to classify the vehicles, count their frequency, track them using unique ID and provide safety measures to the users by flagging the suspicious ones.

Real time Object detection giving all object detected : labels along with all bounding box predictions + Flask live hosted server

Data Augmentation For Object Detection using Deep Learning with PyTorch

Object Detection Implementation with NNStreamer (2020)

Projects I built focused on self driving car

This folder contains data and various code samples related to using object detectors and object segmentation.

argos-back for argos-front

README.mdConfig files for my GitHub profile.

Created API calls, application disclosure, documentation, templates, and code for Enduka Cloud for software development

PHRI1516 - Object Detection

Detecting Dormice in Images Using Object Detection and Transfer Learning

Real-time drowsiness detection using YOLOv5 – detects "awake" and "drowsy" states from webcam input with bounding boxes and confidence scores.