training on coco dataset

[wcwang07]

has anyone ran into issue training on CocoDataset , I have modified on line 220:

elif args.dataset_type == 'coco':
221 # Image preprocessing, normalization for the pretrained resnet
222 transform = transforms.Compose([
223 transforms.RandomCrop(224),
224 transforms.RandomHorizontalFlip(),
225 transforms.ToTensor(),
226 transforms.Normalize((0.485, 0.456, 0.406),
227 (0.229, 0.224, 0.225))])
228 # Load vocabulary wrapper
229 with open('/home/ubuntu/data/coco/vocab.pkl', 'rb') as f:
230 vocab = pickle.load(f)
231 dataset = CocoDataset(dataset_path, json='/home/ubuntu/data/coco/annotations/captions_train2014.json', vocab=vocab,transform=transform)
232 label_file = '/home/ubuntu/data/coco-labels-file.txt'

when i tried to run

337 train(train_loader, net, criterion, optimizer,
338 device=DEVICE, debug_steps=args.debug_steps, epoch=epoch)

got the elements mistach

File "train_ssd.py", line 121, in train
images, boxes, labels = data
ValueError: not enough values to unpack (expected 3, got 2)

tensor data[0] has shape (1,3,224,224)
tensor data[1] has shape (1,15)

i think we are missing data[2]

Any insight is helpful, thank you in advance.

[qfgaohao]

Hi @wcwang07 , "CocoDetection" returns "image" and "targets" instead of "image", "boxes", "labels". You can split "targets" into "boxes" and "labels" to make it work. Plz see "coco.loadAnns" to get the format of "targets".