processing.py | Write Processing sketches in Python | Computer Vision library

I think when you pass multiprocessing you cannot share variables between processes as you would in a single-threaded context. See: https://docs.python.org/3/library/multiprocessing.html#exchanging-objects-between-processes

You may want to check out the Debug page in the Dask docs for general ideas on debugging here: https://docs.dask.org/en/stable/how-to/debug.html#debug

And more specifically the section that talks about logging: https://docs.dask.org/en/stable/how-to/debug.html#logs

I personally found the rerun_exceptions_locally argument to be valuable for quickly debugging errors that happen on Dask workers: https://docs.dask.org/en/stable/how-to/debug.html#rerun-failed-task-locally

In short; Logging (and debugging in general) isn't a trivial thing in a distributed environment. Exceptions often end up killing the worker process and because of that the stack traces or logs might not make it back to you.

I finally find the solution. For people who facing the same trouble:

Here is the command I use for create the binary file:

setup.py does not work in VSCode, you can modify the PYTHONPATH in VSCode through (terminal.integrated.env.*) and/or within an .env file:

The PYTHONPATH environment variable specifies additional locations where the Python interpreter should look for modules. In VS Code, PYTHONPATH can be set through the terminal settings (terminal.integrated.env.*) and/or within an .env file.

When the terminal settings are used, PYTHONPATH affects any tools that are run within the terminal by a user, as well as any action the extension performs for a user that is routed through the terminal such as debugging. However, in this case when the extension is performing an action that isn't routed through the terminal, such as the use of a linter or formatter, then this setting will not have an effect on module look-up.

When PYTHONPATH is set using an .env file, it will affect anything the extension does on your behalf and actions performed by the debugger, but it will not affect tools run in the terminal.

If needed, you can set PYTHONPATH using both methods.

An example of when to use PYTHONPATH would be if you have source code in a src folder and tests in a tests folder. When running tests, however, those tests can't normally access modules in src unless you hard-code relative paths.

To solve this problem, you could add the path to src to PYTHONPATH by creating an .env file within your VS Code workspace.

PYTHONPATH=src

official docs

Since the error is occurring when you attempt to resize, enclose that line in a try/except. When you get the error, continue skips the rest of the current iteration and continues on with the next image file.

You cannot call the method, because it is not a static / class method but instead the method of an instance / object of the class MainApplication.

This means that the cancel_it method's parameter self expects an instance of the class MainApplication to function properly but by calling MainApplication.cancel_it() it receives the class instead as argument and therefore throws an exception.

You could easily call it, by passing a reference to the Mainapplication-instance to your cancel_it method.

Assuming that:

Looks like you are using venv, did you activate it before running your script?

For Linux/Mac you can do the following:

In YAML, it is an error to have multiple identical keys in a mapping. Your root mapping has user two times. This is not allowed.

It is a bit hard to figure out what you want to do, but I believe you're searching for multi-document YAML files:

Move the existing functions(ex. write_to_csv) to different file for example 'utility_functions.py'. Import it in main.py using from utility_functions import write_to_csv. Now you can use the function 'write_to_csv' in main.py as

write_to_csv(all_keys)

Edit In the main.pyfile use from data_extraction import data_extraction instead of import data_extraction

In data_extraction.py file

Remove lines from main import baseurl from main import all_keys

It will throw variable undefined error, you can fix it by passing the variable in the function call.

I am not too sure this is directly related to your issue, but on TF 2.7 your code is not working at all, because all the Keras augmentation layers expect float values and not uint8. So, maybe try casting your data like this: