Trying to load a single image to test on model and getting 'NoneType' error

fastai
1 
from fastai.vision.all import *
from fastai.vision import *
import pandas as pd
from fastdownload import download_url



#IMPORT HEADSHOT MODEL
HEADSHOT_PATH = 'DataCompiler\FramingMLModel\Data\Images\Headshot'

headshot_dls = ImageDataLoaders.from_folder(
    path=HEADSHOT_PATH ,
    item_tfms=Resize(224),
    bs=16,
    batch_tfms=[Normalize.from_stats(*imagenet_stats), RandTransform()],
    valid_pct=0.2,
    num_workers=0
    )

model = vision_learner(dls=headshot_dls, arch=models.resnet50,metrics=[accuracy, error_rate])

headshot_model = model.load(f'model')

url = 'https://www.unh.edu/unhtoday/2019/07/build-your-professional-image-professional-headshot'
image_path = 'DataCompiler\FramingMLModel\TestData\\temp_image.jpg'

download_url(url, image_path, show_progress=False)

path = 'DataCompiler\FramingMLModel\TestData'

test_dls = ImageDataLoaders.from_folder(
    path=path,
    item_tfms=Resize(224),
    bs=1,
    batch_tfms=[Normalize.from_stats(*imagenet_stats), RandTransform()],
    num_workers=0,
    valid_pct=0
    )

preds, _ = headshot_model.get_preds(dl=test_dls)
print(preds)
os.remove('DataCompiler\\TestData\\temp_image')

I am pretty new to FastAI so it may not make sense how I’m approaching the code.

I am trying to load a model I made in another file and test it on a single image to get a prediction. From what I understand, I need to load the original dls, set up the learner with the original dls, and then load the model into the learner.

I am then downloading a random image using download_url() and storing it locally so I can test it with the model. When I use ImageDataLoaders.from_folder() on the folder the new image is stored in, I am getting this error:

types = L(t if is_listy(t) else [t] for t in self.types).concat().unique()
TypeError: 'NoneType' object is not iterable

I don’t really know why this is happening, any advice would be great, thanks.