279 lines
12 KiB
Markdown
279 lines
12 KiB
Markdown
---
|
|
layout: forward
|
|
target: https://developers.google.com/mediapipe/framework/getting_started/troubleshooting
|
|
title: Troubleshooting
|
|
parent: Getting Started
|
|
nav_order: 10
|
|
---
|
|
|
|
# Troubleshooting
|
|
{: .no_toc }
|
|
|
|
1. TOC
|
|
{:toc}
|
|
---
|
|
|
|
## Missing Python binary path
|
|
|
|
The error message:
|
|
|
|
```
|
|
ERROR: An error occurred during the fetch of repository 'local_execution_config_python':
|
|
Traceback (most recent call last):
|
|
File "/sandbox_path/external/org_tensorflow/third_party/py/python_configure.bzl", line 208
|
|
get_python_bin(repository_ctx)
|
|
...
|
|
Repository command failed
|
|
```
|
|
|
|
usually indicates that Bazel fails to find the local Python binary. To solve
|
|
this issue, please first find where the python binary is and then add
|
|
`--action_env PYTHON_BIN_PATH=<path to python binary>` to the Bazel command. For
|
|
example, you can switch to use the system default python3 binary by the
|
|
following command:
|
|
|
|
```
|
|
bazel build -c opt \
|
|
--define MEDIAPIPE_DISABLE_GPU=1 \
|
|
--action_env PYTHON_BIN_PATH=$(which python3) \
|
|
mediapipe/examples/desktop/hello_world
|
|
```
|
|
|
|
## Missing necessary Python packages
|
|
|
|
The error message:
|
|
|
|
```
|
|
ImportError: No module named numpy
|
|
Is numpy installed?
|
|
```
|
|
|
|
usually indicates that certain Python packages are not installed. Please run
|
|
`pip install` or `pip3 install` depending on your Python binary version to
|
|
install those packages.
|
|
|
|
## Fail to fetch remote dependency repositories
|
|
|
|
The error message:
|
|
|
|
```
|
|
ERROR: An error occurred during the fetch of repository 'org_tensorflow':
|
|
java.io.IOException: Error downloading [https://mirror.bazel.build/github.com/tensorflow/tensorflow/archive/77e9ffb9b2bfb1a4f7056e62d84039626923e328.tar.gz, https://github.com/tensorflow/tensorflow/archive/77e9ffb9b2bfb1a4f7056e62d84039626923e328.tar.gz] to /sandbox_path/external/org_tensorflow/77e9ffb9b2bfb1a4f7056e62d84039626923e328.tar.gz: Tried to reconnect at offset 9,944,151 but server didn't support it
|
|
|
|
or
|
|
|
|
WARNING: Download from https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/rules_swift/releases/download/0.12.1/rules_swift.0.12.1.tar.gz failed: class java.net.ConnectException Connection timed out (Connection timed out)
|
|
```
|
|
|
|
usually indicates that Bazel fails to download necessary dependency repositories
|
|
that MediaPipe needs. MediaPipe has several dependency repositories that are
|
|
hosted by Google sites. In some regions, you may need to set up a network proxy
|
|
or use a VPN to access those resources. You may also need to append
|
|
`--host_jvm_args "-DsocksProxyHost=<ip address> -DsocksProxyPort=<port number>"`
|
|
to the Bazel command. See
|
|
[this GitHub issue](https://github.com/google/mediapipe/issues/581#issuecomment-610356857)
|
|
for more details.
|
|
|
|
If you believe that it's not a network issue, another possibility is that some
|
|
resources could be temporarily unavailable, please run `bazel clean --expunge`
|
|
and retry it later. If it's still not working, please file a GitHub issue with
|
|
the detailed error message.
|
|
|
|
## Incorrect MediaPipe OpenCV config
|
|
|
|
The error message:
|
|
|
|
```
|
|
error: undefined reference to 'cv::String::deallocate()'
|
|
error: undefined reference to 'cv::String::allocate(unsigned long)'
|
|
error: undefined reference to 'cv::VideoCapture::VideoCapture(cv::String const&)'
|
|
...
|
|
error: undefined reference to 'cv::putText(cv::InputOutputArray const&, cv::String const&, cv::Point, int, double, cv::Scalar, int, int, bool)'
|
|
```
|
|
|
|
usually indicates that OpenCV is not properly configured for MediaPipe. Please
|
|
take a look at the "Install OpenCV and FFmpeg" sections in
|
|
[Installation](./install.md) to see how to modify MediaPipe's WORKSPACE and
|
|
linux_opencv/macos_opencv/windows_opencv.BUILD files for your local opencv
|
|
libraries. [This GitHub issue](https://github.com/google/mediapipe/issues/666)
|
|
may also help.
|
|
|
|
## Python pip install failure
|
|
|
|
The error message:
|
|
|
|
```
|
|
ERROR: Could not find a version that satisfies the requirement mediapipe
|
|
ERROR: No matching distribution found for mediapipe
|
|
```
|
|
|
|
after running `pip install mediapipe` usually indicates that there is no qualified MediaPipe Python for your system.
|
|
Please note that MediaPipe Python PyPI officially supports the **64-bit**
|
|
version of Python 3.7 to 3.10 on the following OS:
|
|
|
|
- x86_64 Linux
|
|
- x86_64 macOS 10.15+
|
|
- amd64 Windows
|
|
|
|
If the OS is currently supported and you still see this error, please make sure
|
|
that both the Python and pip binary are for Python 3.7 to 3.10. Otherwise,
|
|
please consider building the MediaPipe Python package locally by following the
|
|
instructions [here](python.md#building-mediapipe-python-package).
|
|
|
|
## Python DLL load failure on Windows
|
|
|
|
The error message:
|
|
|
|
```
|
|
ImportError: DLL load failed: The specified module could not be found
|
|
```
|
|
|
|
usually indicates that the local Windows system is missing Visual C++
|
|
redistributable packages and/or Visual C++ runtime DLLs. This can be solved by
|
|
either installing the official
|
|
[vc_redist.x64.exe](https://support.microsoft.com/en-us/topic/the-latest-supported-visual-c-downloads-2647da03-1eea-4433-9aff-95f26a218cc0)
|
|
or installing the "msvc-runtime" Python package by running
|
|
|
|
```bash
|
|
$ python -m pip install msvc-runtime
|
|
```
|
|
|
|
Please note that the "msvc-runtime" Python package is not released or maintained
|
|
by Microsoft.
|
|
|
|
## Native method not found
|
|
|
|
The error message:
|
|
|
|
```
|
|
java.lang.UnsatisfiedLinkError: No implementation found for void com.google.wick.Wick.nativeWick
|
|
```
|
|
|
|
usually indicates that a needed native library, such as `/libwickjni.so` has not
|
|
been loaded or has not been included in the dependencies of the app or cannot be
|
|
found for some reason. Note that Java requires every native library to be
|
|
explicitly loaded using the function `System.loadLibrary`.
|
|
|
|
## No registered calculator found
|
|
|
|
The error message:
|
|
|
|
```
|
|
No registered object with name: OurNewCalculator; Unable to find Calculator "OurNewCalculator"
|
|
```
|
|
|
|
usually indicates that `OurNewCalculator` is referenced by name in a
|
|
[`CalculatorGraphConfig`] but that the library target for OurNewCalculator has
|
|
not been linked to the application binary. When a new calculator is added to a
|
|
calculator graph, that calculator must also be added as a build dependency of
|
|
the applications using the calculator graph.
|
|
|
|
This error is caught at runtime because calculator graphs reference their
|
|
calculators by name through the field `CalculatorGraphConfig::Node:calculator`.
|
|
When the library for a calculator is linked into an application binary, the
|
|
calculator is automatically registered by name through the
|
|
[`REGISTER_CALCULATOR`] macro using the [`registration.h`] library. Note that
|
|
[`REGISTER_CALCULATOR`] can register a calculator with a namespace prefix,
|
|
identical to its C++ namespace. In this case, the calculator graph must also use
|
|
the same namespace prefix.
|
|
|
|
## Out Of Memory error
|
|
|
|
Exhausting memory can be a symptom of too many packets accumulating inside a
|
|
running MediaPipe graph. This can occur for a number of reasons, such as:
|
|
|
|
1. Some calculators in the graph simply can't keep pace with the arrival of
|
|
packets from a realtime input stream such as a video camera.
|
|
2. Some calculators are waiting for packets that will never arrive.
|
|
|
|
For problem (1), it may be necessary to drop some old packets in older to
|
|
process the more recent packets. For some hints, see:
|
|
[`How to process realtime input streams`].
|
|
|
|
For problem (2), it could be that one input stream is lacking packets for some
|
|
reason. A device or a calculator may be misconfigured or may produce packets
|
|
only sporadically. This can cause downstream calculators to wait for many
|
|
packets that will never arrive, which in turn causes packets to accumulate on
|
|
some of their input streams. MediaPipe addresses this sort of problem using
|
|
"timestamp bounds". For some hints see:
|
|
[`How to process realtime input streams`].
|
|
|
|
The MediaPipe setting [`CalculatorGraphConfig::max_queue_size`] limits the
|
|
number of packets enqueued on any input stream by throttling inputs to the
|
|
graph. For realtime input streams, the number of packets queued at an input
|
|
stream should almost always be zero or one. If this is not the case, you may see
|
|
the following warning message:
|
|
|
|
```
|
|
Resolved a deadlock by increasing max_queue_size of input stream
|
|
```
|
|
|
|
Also, the setting [`CalculatorGraphConfig::report_deadlock`] can be set to cause
|
|
graph run to fail and surface the deadlock as an error, such that max_queue_size
|
|
to acts as a memory usage limit.
|
|
|
|
## Graph hangs
|
|
|
|
Many applications will call [`CalculatorGraph::CloseAllPacketSources`] and
|
|
[`CalculatorGraph::WaitUntilDone`] to finish or suspend execution of a MediaPipe
|
|
graph. The objective here is to allow any pending calculators or packets to
|
|
complete processing, and then to shutdown the graph. If all goes well, every
|
|
stream in the graph will reach [`Timestamp::Done`], and every calculator will
|
|
reach [`CalculatorBase::Close`], and then [`CalculatorGraph::WaitUntilDone`]
|
|
will complete successfully.
|
|
|
|
If some calculators or streams cannot reach state [`Timestamp::Done`] or
|
|
[`CalculatorBase::Close`], then the method [`CalculatorGraph::Cancel`] can be
|
|
called to terminate the graph run without waiting for all pending calculators
|
|
and packets to complete.
|
|
|
|
## Output timing is uneven
|
|
|
|
Some realtime MediaPipe graphs produce a series of video frames for viewing as a
|
|
video effect or as a video diagnostic. Sometimes, a MediaPipe graph will produce
|
|
these frames in clusters, for example when several output frames are
|
|
extrapolated from the same cluster of input frames. If the outputs are presented
|
|
as they are produced, some output frames are immediately replaced by later
|
|
frames in the same cluster, which makes the results hard to see and evaluate
|
|
visually. In cases like this, the output visualization can be improved by
|
|
presenting the frames at even intervals in real time.
|
|
|
|
MediaPipe addresses this use case by mapping timestamps to points in real time.
|
|
Each timestamp indicates a time in microseconds, and a calculator such as
|
|
`LiveClockSyncCalculator` can delay the output of packets to match their
|
|
timestamps. This sort of calculator adjusts the timing of outputs such that:
|
|
|
|
1. The time between outputs corresponds to the time between timestamps as
|
|
closely as possible.
|
|
2. Outputs are produced with the smallest delay possible.
|
|
|
|
## CalculatorGraph lags behind inputs
|
|
|
|
For many realtime MediaPipe graphs, low latency is an objective. MediaPipe
|
|
supports "pipelined" style parallel processing in order to begin processing of
|
|
each packet as early as possible. Normally the lowest possible latency is the
|
|
total time required by each calculator along a "critical path" of successive
|
|
calculators. The latency of the a MediaPipe graph could be worse than the ideal
|
|
due to delays introduced to display frames a even intervals as described in
|
|
[Output timing is uneven](#output-timing-is-uneven).
|
|
|
|
If some of the calculators in the graph cannot keep pace with the realtime input
|
|
streams, then latency will continue to increase, and it becomes necessary to
|
|
drop some input packets. The recommended technique is to use the MediaPipe
|
|
calculators designed specifically for this purpose such as
|
|
[`FlowLimiterCalculator`] as described in
|
|
[`How to process realtime input streams`].
|
|
|
|
[`CalculatorGraphConfig`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/calculator.proto
|
|
[`CalculatorGraphConfig::max_queue_size`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/calculator.proto
|
|
[`CalculatorGraphConfig::report_deadlock`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/calculator.proto
|
|
[`REGISTER_CALCULATOR`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/calculator_registry.h
|
|
[`registration.h`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/deps/registration.h
|
|
[`CalculatorGraph::CloseAllPacketSources`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/calculator_graph.h
|
|
[`CalculatorGraph::Cancel`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/calculator_graph.h
|
|
[`CalculatorGraph::WaitUntilDone`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/calculator_graph.h
|
|
[`Timestamp::Done`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/timestamp.h
|
|
[`CalculatorBase::Close`]: https://github.com/google/mediapipe/tree/master/mediapipe/framework/calculator_base.h
|
|
[`FlowLimiterCalculator`]: https://github.com/google/mediapipe/tree/master/mediapipe/calculators/core/flow_limiter_calculator.cc
|
|
[`How to process realtime input streams`]: faq.md#how-to-process-realtime-input-streams
|