I am working on Melanoma Classification task where I have to classify the patients into two categories on the basis of their skin images. I have used efficientnetb3 model (pretrained) with minor transformations. But I am getting nan as the model output while training. What could be the possible reasons?
class MelanomaDataset(Dataset):
def __init__(self, dataframe, image_dir, transforms = None):
self.dataframe = dataframe
self.image_dir = image_dir
self.transforms = transforms
def __len__(self):
return self.dataframe.shape[0]
def __getitem__(self, idx):
img_name = '{}.png'.format(self.dataframe.iloc[idx, 0])
fullname = self.image_dir + img_name
image = cv2.imread(fullname)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
num = self.dataframe.loc[:,'target'].iloc[idx]
label = np.asarray(int_to_label[num])
if self.transforms:
image = self.transforms(image = image)['image']
return image, label