Unsupervised anomaly detection on COCO-style masked objects, comparison of results using various state-of-the-art deep autoencoders
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Updated
Apr 7, 2021 - Python
Unsupervised anomaly detection on COCO-style masked objects, comparison of results using various state-of-the-art deep autoencoders
Image depth and body keypoints detection demo app, written in Python.
echo1-coco-builder provides a faster, safer way to build coco formatted data.
BiDet implement
Tool used to generate anchor-boxes required for training YOLO networks
Create a YOLO-format subset of the COCO dataset
Example of image-based pattern recognition using YOLOv3, COCO and OpenCV.
In this repo, I use Django to create a web application and I use TensorFlow as the backend to do object identification. I deploy my project on AWS Lighsail.
🛠️ Convert file annotation to COCO format
A tool to evaluate and compare object detection models using the coco metrics (https://cocodataset.org/#detection-eval) and tools available by the cocoapi (https://github.com/cocodataset/cocoapi)
A simple python application using opencv, tensorflow and coco models to show some basic object detection.
A simple script that parses masked images to coco format for object segmentation.
Object Detection using YOLO and OpenCV.
Converting GeoJSON annotations from QuPath to COCO style.
Image segmentation implemented using pytorch on a COCO format Dataset of Ingredients with various models including U-NET, U-NET++, SegNet and DeepLabV3+
A repository for comparison of Adam and L-BFGS-B methods using coco benchmark.
Easy AP Calculator for Object Detection
person-detection-CenterNet(trained by coco)
The ready-to-run image segmentation for COCO image format
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