Running VSCode interactive window on WSL with relative imports

I'm trying to visualize plots using pyplot imshow. Windows' WSL does not work with GUIs so the advised way of doing so is via VSCode's interactive window. However, given my project structure,

$projectFolder
├── mycode
│   ├── __init__.py
│   ├── model.py
│   ├── dataset.py
│   ├── train.py
│   └── predict.py
└── vision
    └── references
        └── detection
            ├── utils.py
            ├── transforms.py
            ├── engine.py
            └── etc

the only way I can run my code is using the terminal (python3 -m mycode.predict), but then again nothing is plotted because of WSL. Here are my imports:

import matplotlib.pyplot as plt
import numpy as np
import torch
from dataset import MyDataset
from model import get_instance_segmentation_model
from PIL import Image
from torchvision.transforms import functional as F
from torchvision.utils import draw_bounding_boxes, draw_segmentation_masks
from train import get_transform

from vision.references.detection import transforms as T

I followed this exactly but still get ModuleNotFoundError: No module named 'vision' when trying to run via the VSCode 'play' button and/or as interactive window, even though autocomplete works and nothing is highlighted ("No problems have been detected in the workspace"). What am I doing wrong here? Here's my launch.json:

{
    // Use IntelliSense to learn about possible attributes.
    // Hover to view descriptions of existing attributes.
    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
    "version": "0.2.0",
    "configurations": [
        {
            "name": "Python: Module",
            "type": "python",
            "request": "launch",
            "module": "mycode",
            "env": {"PYTHONPATH": "${workspaceFolder}/vision/"}
        }
    ]
}

I suggest you using .env file. Here is a table which explains the difference between .env and launch.json:

If you use interactive Window, the settings in launch.json will not work.

You can create .env file under your workspace then add "python.envFile": "${workspaceFolder}/.env", to your settings.json.

.env

PYTHONPATH=PATH/TO/YOUR/FOLDER