[Python] MultiLabel Classification Path errors in pytorch

While I am running the following code, it says [Errno 2] No such file or directory: '/content/drive/MyDrive/Image Dataset/images/img_0_7'. But I already have that file or directory in my drive – still it says missing.

Here is the code portion I have written:

class MultiLabelDataset(Dataset):
def __init__(self):

self.labels, self.images = [], []

labels_path = '/content/drive/MyDrive/Image Dataset/Binary Dataset/labels.csv'
images_path = '/content/drive/MyDrive/Image Dataset/images'

df = pd.read_csv(labels_path)
column_names = df.columns.tolist()
df.rename(columns={column_names[1]: 'classes'}, inplace=True)

for index, row in df.iterrows():
last_elements = row.iloc[-10: ].tolist()
self.labels.append(last_elements)

self.labels = np.array(self.labels)

image_names = df['Image_Name'].tolist()

for img_name in image_names:
image_path = os.path.join(images_path, img_name)
image = Image.open(image_path)
image = np.array(image)
if len(image.shape) == 2:
copied_images = [image.copy() for _ in range(3)]
image = np.stack(copied_images, axis=-1)
image = cv2.resize(image, (32, 32))
self.images.append(image)

self.images = np.array(self.images)

def normalize(self):
self.image = self.images / 255.0

def __getitem__(self, index):
return self.images[index], self.labels[index]

def __len__(self):
return len(self.images)

def __getitem__(self, idx):
sample = {'images': self.images[idx], 'labels': self.labels[idx]}
return sample

d = MultiLabelDataset()


I just want to know where I am doing mistakes and I can't find it. How to fix this error?

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