A tool to download and format MS COCO dataset for multilabel classification
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Updated
Jun 11, 2018 - Python
A tool to download and format MS COCO dataset for multilabel classification
Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)
This repository contains code for YOLO v3 Object detection, and is capable of fast object detection. Input can be given through images, videos and webcam input feed.
A collection of semantic segmentation approaches
Performed object detection and logging time periods by deploying YOLO-V3 with transfer learning and fine tuning classifications for all layers of the network. The model is fine-tuned the model using the pre-trained MS-COCO weights and accordingly modified the same for custom dataset.
Civic Issue Detection Dataset from Adversarial Adaptation of Scene Graph Models for Understanding Civic Issues
MS-COCO-ES is a dataset created from the original MS-COCO dataset. This project aims to provide a small subset of the original image captions translated into Spanish by humans annotators. This subset is composed by 20,000 captions of 4,000 images.
Used deep learning to train a CNN + RNN/LSTM on the MS-COCO dataset to automatically generate captions.
labeling tool that allows easy plugin of detection networks that can assist in the labeling process
A deep learning based application which is entitled to help the visually impaired people. The application automatically generates the textual description of what's happening in front of the camera and conveys it to person through audio. It is capable of recognising faces and tell user whether a known person is standing in front of him or not.
Side projects and hands-on work
A system to process visual input on timed frames to produce sensible audio aid in accordance with human information processing limits, using image captioning, semantic text comparison and text-to-speech modules.
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.
[ICCV19] AdaptIS: Adaptive Instance Selection Network, https://arxiv.org/abs/1909.07829
This Repo covers all formats of annotations for Object Detection and can easily convert from one form to another using attached scripts
Using Image Segmentation for identifying free car parking slots
This project extends the existing Mask-RCNN code to generate a Blum Medial Axis from a natural RGB image.
Python dictionary storing object tags for MS-COCO images. Data from 3 different sources (COCO ground truths, VG classifier and Microsoft's VinVL) are availible.
Vision Based Document Layout Detection, Segmentation and context classification using MaskRCNN on Tensorflow-Keras, PyTorch & Detectron2.
Ladder Loss for Coherent Visual-Semantic Embedding, AAAI, 2020
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