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.