outv=cv2.VideoWriter("Tracked-"+str(arg['video']),cv2.VideoWriter_fourcc(*'MP4V'),int(cap.get(5)),(int(cap.get(3)),int(cap.get(4))))

根据你提供的代码，你正在使用OpenCV创建一个视频写入器（VideoWriter）来保存跟踪结果。在这里，你使用的是MP4V编解码器来设置视频写入器的编码格式。

然而，根据错误信息，该编解码器标签可能不被支持，导致无法创建视频写入器。你可以尝试更换编解码器标签来解决这个问题。例如，你可以尝试使用"mp4v"作为编解码器标签：

outv = cv2.VideoWriter("Tracked-" + str(arg['video']), cv2.VideoWriter_fourcc(*'mp4v'), int(cap.get(5)), (int(cap.get(3)), int(cap.get(4))))

这里使用`cv2.VideoWriter_fourcc(*'mp4v')`来设置编解码器为"mp4v"。这样应该可以解决编解码器不支持的问题。如果问题仍然存在，你可能需要安装其他编解码器或尝试其他的编解码器标签。

相关问题

将下面matlab代码function [channel] = preRun(acqResults, settings)%% Initialize all channels ================================================ channel = []; % Clear, create the structure channel.PRN = 0; % PRN number of the tracked satellite channel.acquiredFreq = 0; % Used as the center frequency of the NCO channel.codePhase = 0; % Position of the C/A start channel.codeFreq = 0; % Used as the center frequency of the code NCO channel.status = '-'; % Mode/status of the tracking channel % "-" - "off" - no signal to track % "T" - Tracking state %--- Copy initial data to all channels ------------------------------------ channel = repmat(channel, 1, settings.numberOfChannels); %% Copy acquisition results =============================================== %--- Sort peaks to find strongest signals, keep the peak index information [~, PRNindexes] = sort(acqResults.peakMetric, 2, 'descend'); %--- Load information about each satellite -------------------------------- % Maximum number of initialized channels is number of detected signals, but % not more as the number of channels specified in the settings. for ii = 1:min([settings.numberOfChannels, sum(acqResults.carrFreq ~= 0)]) channel(ii).PRN = PRNindexes(ii); channel(ii).acquiredFreq = acqResults.carrFreq(PRNindexes(ii)); channel(ii).codePhase = acqResults.codePhase(PRNindexes(ii)); channel(ii).codeFreq = settings.codeFreqBasis + ... (channel(ii).acquiredFreq - settings.IF)/... settings.carrFreqBasis * settings.codeFreqBasis; % Set tracking into mode (there can be more modes if needed e.g. pull-in) channel(ii).status = 'T'; end转成python

以下是将该 MATLAB 代码转换为 Python 的代码：

import numpy as np

def preRun(acqResults, settings):
    # Initialize all channels
    channel = {}
    channel['PRN'] = 0
    channel['acquiredFreq'] = 0
    channel['codePhase'] = 0
    channel['codeFreq'] = 0
    channel['status'] = '-'

    # Copy initial data to all channels
    channel = [channel] * settings['numberOfChannels']

    # Copy acquisition results
    # Sort peaks to find strongest signals, keep the peak index information
    PRNindexes = np.argsort(acqResults['peakMetric'])[::-1]

    # Load information about each satellite
    # Maximum number of initialized channels is number of detected signals, but
    # not more as the number of channels specified in the settings.
    for ii in range(min(settings['numberOfChannels'], sum(acqResults['carrFreq'] != 0))):
        channel[ii]['PRN'] = PRNindexes[ii]
        channel[ii]['acquiredFreq'] = acqResults['carrFreq'][PRNindexes[ii]]
        channel[ii]['codePhase'] = acqResults['codePhase'][PRNindexes[ii]]
        channel[ii]['codeFreq'] = settings['codeFreqBasis'] + \
            (channel[ii]['acquiredFreq'] - settings['IF']) / \
            settings['carrFreqBasis'] * settings['codeFreqBasis']
        # Set tracking into mode (there can be more modes if needed e.g. pull-in)
        channel[ii]['status'] = 'T'

    return channel

Unexpected key(s) in state_dict: "classifier.add_block.0.weight", "classifier.add_block.0.bias", "classifier.add_block.1.weight", "classifier.add_block.1.bias", "classifier.add_block.1.running_mean", "classifier.add_block.1.running_var", "classifier.add_block.1.num_batches_tracked", "classifier.classifier.0.weight", "classifier.classifier.0.bias".

这个错误通常表示你正在尝试加载一个模型权重到一个不匹配的模型中。这可能是因为你正在尝试加载的模型和你当前使用的模型有很大的区别，例如改变了网络结构或者层数等。你可以检查一下你的模型结构和加载的权重是否一致，或者尝试重新训练模型以匹配加载的权重。另外，你也可以尝试修改加载权重的代码，只加载你需要的权重。