def test_eval_mstest(self):
cfg = load_config(self.mstest_cfg_file)
trainer = Trainer(cfg, mode='eval')
cfg.weights = 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams'
trainer.load_weights(cfg.weights)
trainer.evaluate()
def run(FLAGS, cfg):
# build trainer
trainer = Trainer(cfg, mode='eval')
# load weights
trainer.load_weights(cfg.weights, 'resume')
# training
trainer.evaluate()
def run(FLAGS, cfg):
# init parallel environment if nranks > 1
init_parallel_env()
# build trainer
trainer = Trainer(cfg, mode='eval')
# load weights
trainer.load_weights(cfg.weights, 'resume')
# training
trainer.evaluate()
def run(FLAGS, cfg):
if FLAGS.json_eval:
logger.info(
"In json_eval mode, PaddleDetection will evaluate json files in "
"output_eval directly. And proposal.json, bbox.json and mask.json "
"will be detected by default.")
json_eval_results(cfg.metric,
json_directory=FLAGS.output_eval,
dataset=cfg['EvalDataset'])
return
# init parallel environment if nranks > 1
init_parallel_env()
# build trainer
trainer = Trainer(cfg, mode='eval')
# load weights
trainer.load_weights(cfg.weights)
# training
trainer.evaluate()