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.
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.
Towards a standardizing apparel data
Mixed vision-language Attention Model that gets better by making mistakes
Create a neural network architecture to automatically generate captions from images.
This project implements a vehicle registration plate detection system using Detectron2, a powerful object detection and segmentation framework built on PyTorch. The project involves training a model on a custom dataset to identify and localize registration plates in images.
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