CarCountingYolov4-DeepSort:基于对象跟踪算法的对象计数算法,带有深度排序和来自Yolov4的检测

上传者: 42111465 | 上传时间: 2022-10-18 09:17:22 | 文件大小: 73.99MB | 文件类型: ZIP
yolov4-deepsort 使用YOLOv4,DeepSort和TensorFlow实现的对象跟踪。 YOLOv4是一种先进的算法,它使用深度卷积神经网络来执行对象检测。 我们可以将YOLOv4的输出输入这些对象检测到Deep SORT(带有Deep Association Metric的简单在线和实时跟踪)中,以创建一个高度精确的对象跟踪器。 关于对象的对象跟踪器的演示 汽车上的对象跟踪器演示 入门 首先,请通过Anaconda或Pip安装适当的依赖项。 我建议使用GPU的人使用Anaconda路由,因为它可以为您配置CUDA工具包版本。 conda(推荐) # Tensorflow CPU conda env create -f conda-cpu.yml conda activate yolov4-cpu # Tensorflow GPU conda env create -

文件下载

资源详情

[{"title":"( 63 个子文件 73.99MB ) CarCountingYolov4-DeepSort:基于对象跟踪算法的对象计数算法,带有深度排序和来自Yolov4的检测","children":[{"title":"CarCountingYolov4-DeepSort-main","children":[{"title":"requirements-gpu.txt <span style='color:#111;'> 102B </span>","children":null,"spread":false},{"title":"convert_tflite.py <span style='color:#111;'> 2.94KB </span>","children":null,"spread":false},{"title":"model_data","children":[{"title":"mars-small128.pb <span style='color:#111;'> 10.72MB </span>","children":null,"spread":false}],"spread":true},{"title":"core","children":[{"title":"config.py <span style='color:#111;'> 1.72KB </span>","children":null,"spread":false},{"title":"backbone.py <span style='color:#111;'> 8.27KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 12.89KB </span>","children":null,"spread":false},{"title":"dataset.py <span style='color:#111;'> 14.07KB </span>","children":null,"spread":false},{"title":"yolov4.py <span style='color:#111;'> 15.98KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-37.pyc <span style='color:#111;'> 9.77KB </span>","children":null,"spread":false},{"title":"config.cpython-37.pyc <span style='color:#111;'> 1.27KB </span>","children":null,"spread":false},{"title":"yolov4.cpython-37.pyc <span style='color:#111;'> 9.05KB </span>","children":null,"spread":false},{"title":"backbone.cpython-37.pyc <span style='color:#111;'> 3.96KB </span>","children":null,"spread":false},{"title":"common.cpython-37.pyc <span style='color:#111;'> 2.41KB </span>","children":null,"spread":false}],"spread":true},{"title":"common.py <span style='color:#111;'> 2.91KB </span>","children":null,"spread":false}],"spread":true},{"title":"convert_trt.py <span style='color:#111;'> 4.15KB </span>","children":null,"spread":false},{"title":"conda-cpu.yml <span style='color:#111;'> 225B </span>","children":null,"spread":false},{"title":"requirements.txt <span style='color:#111;'> 98B </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"tools","children":[{"title":"generate_detections.py <span style='color:#111;'> 8.02KB </span>","children":null,"spread":false},{"title":"freeze_model.py <span style='color:#111;'> 8.49KB </span>","children":null,"spread":false}],"spread":true},{"title":"conda-gpu.yml <span style='color:#111;'> 269B </span>","children":null,"spread":false},{"title":"save_model.py <span style='color:#111;'> 2.60KB </span>","children":null,"spread":false},{"title":"object_tracker.py <span style='color:#111;'> 10.34KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 7.45KB </span>","children":null,"spread":false},{"title":"outputs","children":[{"title":"demo.avi <span style='color:#111;'> 9.40MB </span>","children":null,"spread":false},{"title":"cars.avi <span style='color:#111;'> 11.93MB </span>","children":null,"spread":false}],"spread":false},{"title":"data","children":[{"title":"classes","children":[{"title":"voc.names <span style='color:#111;'> 153B </span>","children":null,"spread":false},{"title":"yymnist.names <span style='color:#111;'> 30B </span>","children":null,"spread":false},{"title":"coco.names <span style='color:#111;'> 707B </span>","children":null,"spread":false}],"spread":false},{"title":"video","children":[{"title":"test.mp4 <span style='color:#111;'> 3.54MB </span>","children":null,"spread":false},{"title":"cars.mp4 <span style='color:#111;'> 6.69MB </span>","children":null,"spread":false}],"spread":false},{"title":"helpers","children":[{"title":"cars.gif <span style='color:#111;'> 12.09MB </span>","children":null,"spread":false},{"title":"filter_classes.PNG <span style='color:#111;'> 8.09KB </span>","children":null,"spread":false},{"title":"custom_result.png <span style='color:#111;'> 976.44KB </span>","children":null,"spread":false},{"title":"custom_config.png <span style='color:#111;'> 26.57KB </span>","children":null,"spread":false},{"title":"performance.png <span style='color:#111;'> 146.78KB </span>","children":null,"spread":false},{"title":"demo.gif <span style='color:#111;'> 8.55MB </span>","children":null,"spread":false},{"title":"all_classes.gif <span style='color:#111;'> 8.60MB </span>","children":null,"spread":false}],"spread":false},{"title":"dataset","children":[{"title":"val2017.txt <span style='color:#111;'> 1002.05KB </span>","children":null,"spread":false},{"title":"val2014.txt <span style='color:#111;'> 8.32MB </span>","children":null,"spread":false}],"spread":false},{"title":"anchors","children":[{"title":"basline_anchors.txt <span style='color:#111;'> 124B </span>","children":null,"spread":false},{"title":"basline_tiny_anchors.txt <span style='color:#111;'> 44B </span>","children":null,"spread":false},{"title":"yolov3_anchors.txt <span style='color:#111;'> 67B </span>","children":null,"spread":false},{"title":"yolov4_anchors.txt <span style='color:#111;'> 70B </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"deep_sort","children":[{"title":"preprocessing.py <span style='color:#111;'> 2.00KB </span>","children":null,"spread":false},{"title":"detection.py <span style='color:#111;'> 1.60KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 28B </span>","children":null,"spread":false},{"title":"tracker.py <span style='color:#111;'> 5.36KB </span>","children":null,"spread":false},{"title":"linear_assignment.py <span style='color:#111;'> 7.85KB </span>","children":null,"spread":false},{"title":"iou_matching.py <span style='color:#111;'> 2.84KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"preprocessing.cpython-37.pyc <span style='color:#111;'> 1.88KB </span>","children":null,"spread":false},{"title":"tracker.cpython-37.pyc <span style='color:#111;'> 5.26KB </span>","children":null,"spread":false},{"title":"linear_assignment.cpython-37.pyc <span style='color:#111;'> 6.78KB </span>","children":null,"spread":false},{"title":"iou_matching.cpython-37.pyc <span style='color:#111;'> 2.77KB </span>","children":null,"spread":false},{"title":"nn_matching.cpython-37.pyc <span style='color:#111;'> 5.88KB </span>","children":null,"spread":false},{"title":"detection.cpython-37.pyc <span style='color:#111;'> 1.99KB </span>","children":null,"spread":false},{"title":"kalman_filter.cpython-37.pyc <span style='color:#111;'> 6.51KB </span>","children":null,"spread":false},{"title":"__init__.cpython-37.pyc <span style='color:#111;'> 138B </span>","children":null,"spread":false},{"title":"track.cpython-37.pyc <span style='color:#111;'> 5.42KB </span>","children":null,"spread":false}],"spread":false},{"title":"track.py <span style='color:#111;'> 5.14KB </span>","children":null,"spread":false},{"title":"kalman_filter.py <span style='color:#111;'> 7.83KB </span>","children":null,"spread":false},{"title":"nn_matching.py <span style='color:#111;'> 5.51KB </span>","children":null,"spread":false}],"spread":false},{"title":"object_tracker (3).py <span style='color:#111;'> 13.94KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明