master 1Branch Tags Code This branch is up to date withdongdonghy/Detection-PyTorch-Notebook:master. Folders and files Name Last commit message Last commit date Latest commit dongdonghy Update Evaluator.py Mar 2
《深度学习之PyTorch物体检测实战》是一本详细介绍如何利用PyTorch框架进行物体检测的实用书籍。书中通过DetectionPyTorchNotebook代码的讲解,系统地介绍了目标检测领域的基本概念、常用数据集的处理方法以及各种经典物体检测模型的实现原理和代码实践。读者可以通过学习这
熟悉TensorFlow的人都知道,tf在Github上的主页是: https://github.com/tensorflow , 然后这个主页下又有两个比较重要的repo(看star数就知道了),分别是TensorFlow的源代码repo:tensorflow/tensorflow,还有一个tensorflow/models。 后者tensorflow/models是Google官方用TensorFlow做的各种各样的模型,相当于示例代码,比如用于图...
多线程建议每个线程一个 Predictor Jupyter Notebook 附上可以直接运行的 notebook:d2l/paddledetection.ipynb at master · hligaty/d2l (github.com)。Maven 下载依赖比较慢,建议手动下载依赖放到/${HOME}/.ivy2/cache/下。 推荐 李沐大大有一本动手学深度学习的书,有 python 语言 pytorch、mxnet 等框架的版本...
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MMTracking is an open source video perception toolbox by PyTorch. It is a part ofOpenMMLabproject. The master branch works withPyTorch1.5+. Major features The First Unified Video Perception Platform We are the first open source toolbox that unifies versatile video perception tasks include video ob...
tensorflow官方GitHub:https://github.com/tensorflow/models/tree/master/research/object_detection 背景: 将官方Object-Detection用PyCharm进行构建。官方给的实例可以用jupyter notebook直接运行object_detection_tutorial.ipynb来完成object的...Tensorflow Object Detection API Tensorflow Object Detection API Tensorflow ...
It was written using Python language, and the framework used is PyTorch. It is in itself a collection of object detection models. From tiny models capable of giving real-time FPS on edge devices to huge and accurate models meant for cloud GPU deployments. It has almost everything one might...
and should not require complex libraries for training and inference. DETR is very simple to implement and experiment with, and we provide astandalone Colab Notebookshowing how to do inference with DETR in only a few lines of PyTorch code. Training code follows this idea - it is not a libra...
Expanded Deep Learning Support: Integrates 12 modern neural models into a single PyTorch-based framework, bringing the total number of outlier detection methods to 45. Enhanced Performance and Ease of Use: Models are optimized for efficiency and consistent performance across different datasets. LLM-...