print_single_error(epoch_idx, loss_fn.show(), metric_fn.show())
lr_scheduler.step()
if config.TEST:
test(model, config_test)
if config.SAVE_MODEL:
save_checkpoint(epoch_idx, model, output_dir)
if not config.TEST:
test(model, config_test)
if not config.SAVE_MODEL:
save_checkpoint(epoch_idx, model, output_dir)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='train model')
parser.add_argument('--train',
type=str,
default="train.yaml",
help='train config file')
parser.add_argument('--test',
type=str,
default="test.yaml",
help='test config file')
opt = parser.parse_args()
config_train = parse_train_config(read_yaml_config(opt.train))
config_test = parse_test_config(read_yaml_config(opt.test))
train(config_train, config_test)
A.Normalize(),
M.MyToTensorV2(),
],
additional_targets={
'right_img': 'image',
})
dataset = LoadImages(config.JSON, transform=transform)
if not model:
model = Model()
model = model.to(DEVICE)
_, model = load_checkpoint(model, config.CHECKPOINT_FILE, DEVICE)
model.eval()
for img, predictions, path in generatePredictions(model, dataset):
plot_predictions([img], predictions, [path])
save_predictions([img], predictions, [path])
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='run inference on model')
parser.add_argument('--detect',
type=str,
default="detect.yaml",
help='detect config file')
opt = parser.parse_args()
config_detect = parse_detect_config(read_yaml_config(opt.detect))
detect(config=config_detect)
batch_size=config.BATCH_SIZE,
transform=transform,
workers=config.WORKERS,
pin_memory=config.PIN_MEMORY,
shuffle=config.SHUFFLE)
if not model:
model = Model()
model = model.to(DEVICE)
epoch, model = load_checkpoint(model, config.CHECKPOINT_FILE, DEVICE)
loss_fn = LossFunction()
metric_fn = MetricFunction(config.BATCH_SIZE)
model.eval()
run_test(model, dataloader, loss_fn, metric_fn)
print_single_error(epoch, loss_fn.show(), metric_fn.show())
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='test model')
parser.add_argument('--test',
type=str,
default="test.yaml",
help='test config file')
opt = parser.parse_args()
config_test = parse_test_config(read_yaml_config(opt.test))
test(config=config_test)