[ERROR] found no matching timestamps between reference and V101stereo.tum with max. time diff 0.01 (s) and time offset 0.0 (s)

这个错误信息是指在执行某个程序时，发现参考时间戳和V101stereo.tum文件中的时间戳之间没有匹配的记录。可能的原因包括参考时间戳或V101stereo.tum文件中的错误时间戳，或者两者之间的时间差超过了最大时间差限制。建议检查参考时间戳和V101stereo.tum文件的时间戳格式和值是否正确，并尝试调整最大时间差限制以解决问题。

相关问题

ERROR: No matching distribution found for torch.version.cuda

"ERROR: No matching distribution found for torch.version.cuda"这个错误通常是由于您的PyTorch版本与CUDA版本不兼容导致的。您可以尝试升级或降级PyTorch版本，以使其与您的CUDA版本匹配。您还可以检查您的CUDA版本是否正确安装并配置正确。如果您使用的是GPU版本的PyTorch，则必须正确安装和配置CUDA才能使用GPU进行加速计算。

ERROR: No matching distribution found for tensorflow.contrib.rnn.python.ops

As of TensorFlow 2.0, the `tensorflow.contrib` module has been removed. Therefore, you cannot install the `tensorflow.contrib.rnn.python.ops` package.

Instead, you should use the built-in `tf.keras.layers` module to create recurrent neural networks. For example:

import tensorflow as tf

model = tf.keras.Sequential([
  tf.keras.layers.LSTM(64),
  tf.keras.layers.Dense(10)
])

This code creates a model with an LSTM layer with 64 units and a dense layer with 10 units. You can then train this model using the `fit` method:

model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=10, validation_data=(x_test, y_test))

This code compiles the model with the `categorical_crossentropy` loss function, the `adam` optimizer, and the `accuracy` metric. It then trains the model for 10 epochs on the training data `x_train` and `y_train`, and validates the model on the test data `x_test` and `y_test`.