dest="devices",
help="GPU id of running. if more than one, use spacing to separate.",
nargs="+",
default=[0],
type=int)
args = parser.parse_args()
devices = [str(x) for x in args.devices]
train(flags=["--cfg", cfg, "--use_gpu", "--log_steps", "10"],
options=[
"SOLVER.NUM_EPOCHS", "1", "TRAIN.PRETRAINED_MODEL_DIR",
test_model, "TRAIN.MODEL_SAVE_DIR", saved_model,
"DATASET.TRAIN_FILE_LIST",
os.path.join(DATASET_PATH, "mini_pet", "file_list",
"train_list.txt"), "DATASET.VAL_FILE_LIST",
os.path.join(DATASET_PATH, "mini_pet", "file_list",
"val_list.txt"), "DATASET.TEST_FILE_LIST",
os.path.join(DATASET_PATH, "mini_pet", "file_list",
"test_list.txt"), "DATASET.DATA_DIR",
os.path.join(DATASET_PATH, "mini_pet"), "BATCH_SIZE", "1"
],
devices=devices)
eval(flags=["--cfg", cfg, "--use_gpu"],
options=[
"TEST.TEST_MODEL",
os.path.join(saved_model, "final"), "DATASET.VAL_FILE_LIST",
os.path.join(DATASET_PATH, "mini_pet", "file_list",
"val_list.txt"), "DATASET.DATA_DIR",
os.path.join(DATASET_PATH, "mini_pet")
],
default=0,
type=int)
args = parser.parse_args()
devices = [str(x) for x in args.devices]
export_model(
flags=["--cfg", cfg],
options=[
"TEST.TEST_MODEL", test_model, "FREEZE.SAVE_DIR", freeze_save_dir
],
devices=devices)
# Final eval results should be #image=500 acc=0.9615 IoU=0.7804
eval(
flags=["--cfg", cfg, "--use_gpu"],
options=["TEST.TEST_MODEL", test_model],
devices=devices)
vis(flags=["--cfg", cfg, "--use_gpu", "--local_test", "--vis_dir", vis_dir],
options=["TEST.TEST_MODEL", test_model],
devices=devices)
train(
flags=["--cfg", cfg, "--use_gpu", "--log_steps", "10"],
options=[
"SOLVER.NUM_EPOCHS", "1", "TRAIN.PRETRAINED_MODEL", test_model,
"TRAIN.MODEL_SAVE_DIR", saved_model
],
devices=devices)