Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.

A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.

Towards a standardizing apparel data

Python library for Object Detection metrics.

🧮 A deep learning object detection model built using SSD ResNet101 V1 FPN 640x640 🤖 in conjunction with TensorFlow object detection API. Trained on a custom dataset (300+ images) for 10 different labels, the model detects tile colors on Rubik's cube face with 98-100% accuracy 🎯 and only 0.2 total loss.

Mixed vision-language Attention Model that gets better by making mistakes

Create a neural network architecture to automatically generate captions from images.