def METHOD_NAME(self, index: int):
    labels = []
    boxes = []
    with open(self.targets[index]) as inp:
        content = csv.reader(inp, delimiter=" ")
        for line in content:
            if line[0] in ['Pedestrian', 'Person_sitting', 'Cyclist']:
                boxes.append([float(x) for x in line[4:8]])
                labels.append(1) # Re-label Pedestrian, Person_sitting, Cyclist to Person=1
            if line[0] in ['Car', 'Truck', 'Van', 'Tram']:
                boxes.append([float(x) for x in line[4:8]])
                labels.append(2) # Re-label Car, Truck, Van, Tram to Vehicle=2
    boxes = torch.FloatTensor(boxes)  
    target = {}
    target['image_id'] = torch.tensor([index])
    target['boxes'] = boxes
    target['labels'] = torch.tensor(labels)
    target['area'] = (boxes[:, 3] - boxes[:, 1]) * (boxes[:, 2] - boxes[:, 0])
    target['iscrowd'] = torch.zeros((len(target['labels']),), dtype=torch.int64)
    return target