Showing 1-17 of 17 projects
Reusable computer vision tools for developers
A Python library that provides the most popular metrics used to evaluate object detection algorithms.
A powerful TensorFlow implementation of the Faster R-CNN object detection algorithm.
An open-source tool for labeling images and training computer vision models using a variety of popular detection models.
A Python library for evaluating the performance of neural networks for object detection.
A pretrained PyTorch implementation of the DeepLabV3 and DeepLabV3+ semantic segmentation models for Pascal VOC and Cityscapes datasets.
A computer vision library for training and deploying deep learning models, with support for popular datasets and tasks.
A PyTorch implementation of the Faster R-CNN object detection algorithm that can be trained on VOC dataset.
A PyTorch implementation of the YOLOv4 object detection model with support for various attention mechanisms and mobile models.
A PyTorch-based framework for reproducible deep learning studies with 26 knowledge distillation methods.
A PyTorch implementation of the EfficientDet object detection model for high-performance computer vision tasks.
Minimal documentation framework powered by React and Vite for vibe coders building with AI tools.
DeepLab-ResNet reimplementation in TensorFlow for semantic image segmentation.
A comprehensive Python library for evaluating object detection models using various metrics like mAP, AR, and STT-AP.
This Python project provides utilities to convert datasets to COCO and VOC formats for object detection tasks.
PyTorch re-implementation of DeepLab v2 for semantic segmentation on COCO-Stuff and PASCAL VOC datasets.
A fast and simple image labeling/annotation tool with support for multiple formats like COCO, PASCAL VOC, and more.
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