I am trying to build an AI image classifier, using a youtube guide. When I run my program (unfinished) it does not open up the image. (PYTHON)

I am trying to build an AI image classifier using a youtube guide for a school project. Here is the link: https://www.youtube.com/watch?v=oEKg_jiV1Ng&t=727s

At this stage, I am not done, but when I run my main.py I get the following error:

Traceback (most recent call last):  File "c:\xxx\xx\xx\xx\newai\main.py", line 19, in <module>    for img_path in os.listdir(os.path.join(dir_, category)):NotADirectoryError: [WinError 267] The directory name is invalid: 'C:/xx/xx/xx/xx/newai\\Data\\Blue-Squares\\BlueSquare (1).jpg'

I also get this, but I don't think it matters much to the project personally. (Maybe it does, I just assume since it works in the video it should still work as the video is recent.) :

:\XX\XX\XX\XX\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\torchvision\models\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.  warnings.warn(C:\XX\XX\XX\XX\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\torchvision\models\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.  warnings.warn(msg)

On the video, when he runs it at this stage it prints the keys and runs fine.

Here is my full code:

from img2vec_pytorch import Img2Vecimport osfrom PIL import Image# prepare dataimg2vec = Img2Vec()data_dir = 'C:/XX/XX/XX/XX/newai'train_dir = os.path.join(data_dir, r'Data', r'Blue-Squares')val_dir = os.path.join(data_dir, r'Data', r'Red-Triangles')data = {}for j, dir_ in enumerate([train_dir, val_dir]):    features = []    labels = []    for category in os.listdir(dir_):        for img_path in os.listdir(os.path.join(dir_, category)):            img_path_ = os.path.join(dir_, category, img_path)            img = Image.open(img_path_)            img_features = img2vec.get_vec(img)            features.append(img_features)            labels.append(category)    data[['training_data', 'validation_data'][j]] = features    data[['training_labels', 'validation_labels'][j]] = labelsprint(data.keys())# train model# test performance# save the model

I tried:Copy and pasting the youtubers code and using exactly that, swapping out paths, Changing folders, Changing image names, changing how its set up, googling errors, etc. I know the image isn't a directory, so I understand that, I just don't get what to change. Any feedback would be greatly appreciated.