yolov5 model while trying to create a confusion matrix, I encountered an issue. Please help.

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code :
import torch
from torch.utils.data import DataLoader
from torchvision import transforms
from torchvision.datasets import ImageFolder
from sklearn.metrics import confusion_matrix, classification_report
import numpy as np
from tqdm import tqdm
from PIL import Image

data_dir = "/content/testdataset"

transform = transforms.Compose([
transforms.Resize((224, 224)),
transforms.ToTensor(),
])

dataset = ImageFolder(data_dir, transform=transform)
dataloader = DataLoader(dataset, batch_size=32, shuffle=False)
print(dataset)

output :
Dataset ImageFolder
Number of datapoints: 1491
Root location: /content/testdataset
StandardTransform
Transform: Compose(
Resize(size=(224, 224), interpolation=bilinear, max_size=None, antialias=warn)
ToTensor()
)

I was fine until now, but I'm encountering issues from this point onward.

code :
model.eval()

all_predictions = []
all_labels = []

for inputs, labels in tqdm(dataloader, desc="Evaluating"):
# 모델 예측 수행
with torch.no_grad():
outputs = model(inputs)

----> 8 for inputs, labels in tqdm(dataloader, desc="Evaluating"):
UnidentifiedImageError: cannot identify image file <_io.BufferedReader name='/content/testdataset/with_mask/1 (371).jpeg'>

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