multiscale model has lower IOU performance

[ymli39]

Hi @speedinghzl ,

I used your pytorch deeplab v2 implementation, same setting, with torch version of 0.4.0, I used batch size of 16 to train the multi-scale model and evaluated at evaluate.py. However I checked iteration at 10000, 20000, 30000... the meanIOU performance remains at 0.55~0.59.
Could you give me any comments for what I did wrong?
Here is the parameter I used:

BATCH_SIZE = 16
ITER_SIZE = 10
IGNORE_LABEL = 255
INPUT_SIZE = '321,321'
LEARNING_RATE = 2.5e-4
NUM_STEPS = 500000
POWER = 0.9
RANDOM_SEED = 1234
RESTORE_FROM = './model/MS_DeepLab_resnet_pretrained_COCO_init.pth'
SAVE_NUM_IMAGES = 2
SAVE_PRED_EVERY = 50
SNAPSHOT_DIR = './snapshots_msc/'
WEIGHT_DECAY = 0.0005

Thank you for your help!

[speedinghzl]

@ymli39 You need to try train.py rather than train_msc.py.