CNN model accuracy

Here is how i fixed the classes not corresponding to each other, code is done with Pytorch, most of my function are custom ones but I wrote the equivalent in comments :

def main():
    modelPath = '../Results/BestModel/model.ntw'
    model = Om.openModel(modelPath)  # torch.load(modelPath)

    dataPath = 'food-101/images'  # DataSet path
    listClasses = os.listdir(dataPath)  # List of classes, here each folder in dataPath is a class

    dicClasses = {}

    for i, imClass in enumerate(listClasses):
        if i % 5 == 0:
            print(str(i) + ' / ' + str(len(listClasses)))
        res = []
        lIm = os.listdir(os.path.join(dataPath, imClass))
        random.shuffle(lIm)
        for imName in lIm[:20]:  # Take 20 images of each class
            im = Om.loadImage(os.path.join(dataPath, imClass, imName))  # Loading image with correct transforms applied
            res.append(model(im).cpu().numpy())  # Store the result of the prediction
        resmed = np.mean(res, 0)[0]  # Sum all predictions
        r = indexesMax(resmed, 1)  # function is the same as torch.argmax(resmed).
        dicClasses[imClass] = r

    print(dicClasses)