(
self,
dataset,
class_num,
norm_mean,
norm_std,
network,
multi_scales,
is_flip,
devices,
config,
verbose=False,
save_path=None,
show_image=False,
)
| 17 | |
| 18 | class Evaluator(object): |
| 19 | def __init__( |
| 20 | self, |
| 21 | dataset, |
| 22 | class_num, |
| 23 | norm_mean, |
| 24 | norm_std, |
| 25 | network, |
| 26 | multi_scales, |
| 27 | is_flip, |
| 28 | devices, |
| 29 | config, |
| 30 | verbose=False, |
| 31 | save_path=None, |
| 32 | show_image=False, |
| 33 | ): |
| 34 | self.eval_time = 0 |
| 35 | self.config = config |
| 36 | self.dataset = dataset |
| 37 | self.ndata = self.dataset.get_length() |
| 38 | self.class_num = class_num |
| 39 | self.norm_mean = norm_mean |
| 40 | self.norm_std = norm_std |
| 41 | self.multi_scales = multi_scales |
| 42 | self.is_flip = is_flip |
| 43 | self.network = network |
| 44 | self.devices = devices |
| 45 | |
| 46 | self.context = mp.get_context("spawn") |
| 47 | self.val_func = None |
| 48 | self.results_queue = self.context.Queue(self.ndata) |
| 49 | |
| 50 | self.verbose = verbose |
| 51 | self.save_path = save_path |
| 52 | if save_path is not None: |
| 53 | ensure_dir(save_path) |
| 54 | self.show_image = show_image |
| 55 | |
| 56 | def run(self, model_path, model_indice, log_file, log_file_link): |
| 57 | """There are four evaluation modes: |
nothing calls this directly
no test coverage detected