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在UCF101上使用3D CNN/CNN + RNN进行视频分类/动作识别的教程-python源码

上传者： 42106299 | 上传时间： 2021-09-01 13:46:32 | 文件大小： 8.78MB | 文件类型： ZIP
在UCF101上使用3D CNN/CNN + RNN进行视频分类/动作识别的教程 视频分类 该存储库使用 UCF101 和 PyTorch 为视频分类（或动作识别）构建了一个快速而简单的代码。 视频被视为一个 3D 图像或几个连续的 2D 图像（图 1）。 下面是两个简单的神经网络模型：数据集 UCF101 共有来自 101 个动作的 13,320 个视频。 视频具有不同的时间长度（帧）和不同的 2d 图像大小； 最短的是28帧。 为了避免像 OpenCV 或 FFmpeg 这样的帧提取和转换等痛苦的视频预处理，这里我直接使用了来自 feichtenhofer 的预处理数据集。 如果您想从头开始转换或提取视频帧，这里有一些不错的教程：https://pythonprogramming.net/loading-video-python-opencv-tutorial/ https://www.pyimagesearch.com/2017/02/ 06/faster-video-file-fps-with-cv2-videocapture-and-opencv/ 模型 1. 3

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