#计算机科学#We write your reusable computer vision tools. 💜
Most popular metrics used to evaluate object detection algorithms.
翻译 - 最流行的度量标准,用于评估对象检测算法。
#计算机科学#Free to use online tool for labelling photos. https://makesense.ai
翻译 - 免费使用在线工具为照片加标签。 https://makesense.ai
#计算机科学#mean Average Precision - This code evaluates the performance of your neural net for object recognition.
翻译 - 平均平均精度-此代码评估神经网络用于对象识别的性能。
Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes
#计算机科学#CVNets: A library for training computer vision networks
#自然语言处理#A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemente...
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
翻译 - 实施EfficientDet:PyTorch中的可扩展且高效的对象检测
DeepLab-ResNet rebuilt in TensorFlow
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 ...
#计算机科学#To speedup and simplify image labeling/ annotation process with multiple supported formats.
翻译 - 为了加快和简化具有多种受支持格式的图像标记/注释过程。
Label images and video for Computer Vision applications
PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, RESA, LSTR, LaneATT, BézierLaneNet...) based on PyTorch with fast training, visualization, benchm...
DeepLabv3+ built in TensorFlow
#安卓#Real-time object detection on Android using the YOLO network with TensorFlow
#计算机科学#DeepLab resnet v2 model in pytorch
#数据仓库#Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.
#计算机科学#[CVPR'22 & IJCV'24] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels & Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentation
This repository contains the source code of our work on designing efficient CNNs for computer vision