From 8262d4614331aba38e39d1e6d3546f429764ac91 Mon Sep 17 00:00:00 2001
From: Kai Chen <chenkaidev@gmail.com>
Date: Thu, 4 Oct 2018 21:05:39 +0800
Subject: [PATCH] adapt to mmcv api changes
---
mmdet/core/eval/eval_hooks.py | 2 +-
mmdet/core/utils/dist_utils.py | 2 +-
mmdet/core/utils/hooks.py | 2 +-
mmdet/core/utils/misc.py | 3 ++-
mmdet/datasets/loader/build_loader.py | 2 +-
mmdet/datasets/transforms.py | 2 +-
mmdet/models/backbones/resnet.py | 2 +-
mmdet/models/builder.py | 4 ++--
tools/test.py | 2 +-
tools/train.py | 2 +-
10 files changed, 12 insertions(+), 11 deletions(-)
diff --git a/mmdet/core/eval/eval_hooks.py b/mmdet/core/eval/eval_hooks.py
index 3439ee0..c02aec9 100644
--- a/mmdet/core/eval/eval_hooks.py
+++ b/mmdet/core/eval/eval_hooks.py
@@ -6,7 +6,7 @@ import time
import mmcv
import numpy as np
import torch
-from mmcv.torchpack import Hook, obj_from_dict
+from mmcv.runner import Hook, obj_from_dict
from pycocotools.cocoeval import COCOeval
from torch.utils.data import Dataset
diff --git a/mmdet/core/utils/dist_utils.py b/mmdet/core/utils/dist_utils.py
index 07b1592..fc102c6 100644
--- a/mmdet/core/utils/dist_utils.py
+++ b/mmdet/core/utils/dist_utils.py
@@ -6,7 +6,7 @@ import torch.multiprocessing as mp
import torch.distributed as dist
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
from torch.nn.utils import clip_grad
-from mmcv.torchpack import Hook, OptimizerHook
+from mmcv.runner import Hook, OptimizerHook
def init_dist(launcher, backend='nccl', **kwargs):
diff --git a/mmdet/core/utils/hooks.py b/mmdet/core/utils/hooks.py
index 72eb343..7186ad7 100644
--- a/mmdet/core/utils/hooks.py
+++ b/mmdet/core/utils/hooks.py
@@ -1,5 +1,5 @@
import torch
-from mmcv.torchpack import Hook
+from mmcv.runner import Hook
class EmptyCacheHook(Hook):
diff --git a/mmdet/core/utils/misc.py b/mmdet/core/utils/misc.py
index fd8211e..262f168 100644
--- a/mmdet/core/utils/misc.py
+++ b/mmdet/core/utils/misc.py
@@ -12,7 +12,8 @@ def tensor2imgs(tensor, mean=(0, 0, 0), std=(1, 1, 1), to_rgb=True):
imgs = []
for img_id in range(num_imgs):
img = tensor[img_id, ...].cpu().numpy().transpose(1, 2, 0)
- img = mmcv.imdenorm(img, mean, std, to_bgr=to_rgb).astype(np.uint8)
+ img = mmcv.imdenormalize(
+ img, mean, std, to_bgr=to_rgb).astype(np.uint8)
imgs.append(np.ascontiguousarray(img))
return imgs
diff --git a/mmdet/datasets/loader/build_loader.py b/mmdet/datasets/loader/build_loader.py
index 34fe2d2..70f4399 100644
--- a/mmdet/datasets/loader/build_loader.py
+++ b/mmdet/datasets/loader/build_loader.py
@@ -1,6 +1,6 @@
from functools import partial
-from mmcv.torchpack import get_dist_info
+from mmcv.runner import get_dist_info
from torch.utils.data import DataLoader
from .collate import collate
diff --git a/mmdet/datasets/transforms.py b/mmdet/datasets/transforms.py
index 6cdba4e..19bfe05 100644
--- a/mmdet/datasets/transforms.py
+++ b/mmdet/datasets/transforms.py
@@ -31,7 +31,7 @@ class ImageTransform(object):
def __call__(self, img, scale, flip=False):
img, scale_factor = mmcv.imrescale(img, scale, return_scale=True)
img_shape = img.shape
- img = mmcv.imnorm(img, self.mean, self.std, self.to_rgb)
+ img = mmcv.imnormalize(img, self.mean, self.std, self.to_rgb)
if flip:
img = mmcv.imflip(img)
if self.size_divisor is not None:
diff --git a/mmdet/models/backbones/resnet.py b/mmdet/models/backbones/resnet.py
index fbb3f09..458de92 100644
--- a/mmdet/models/backbones/resnet.py
+++ b/mmdet/models/backbones/resnet.py
@@ -3,7 +3,7 @@ import math
import torch.nn as nn
import torch.utils.checkpoint as cp
-from mmcv.torchpack import load_checkpoint
+from mmcv.runner import load_checkpoint
def conv3x3(in_planes, out_planes, stride=1, dilation=1):
diff --git a/mmdet/models/builder.py b/mmdet/models/builder.py
index 4bbc94a..bdf0ac3 100644
--- a/mmdet/models/builder.py
+++ b/mmdet/models/builder.py
@@ -1,4 +1,4 @@
-from mmcv import torchpack as tp
+from mmcv.runner import obj_from_dict
from torch import nn
from . import (backbones, necks, roi_extractors, rpn_heads, bbox_heads,
@@ -11,7 +11,7 @@ __all__ = [
def _build_module(cfg, parrent=None, default_args=None):
- return cfg if isinstance(cfg, nn.Module) else tp.obj_from_dict(
+ return cfg if isinstance(cfg, nn.Module) else obj_from_dict(
cfg, parrent, default_args)
diff --git a/tools/test.py b/tools/test.py
index 4c87f4e..f1fb9cd 100644
--- a/tools/test.py
+++ b/tools/test.py
@@ -2,7 +2,7 @@ import argparse
import torch
import mmcv
-from mmcv.torchpack import load_checkpoint, parallel_test, obj_from_dict
+from mmcv.runner import load_checkpoint, parallel_test, obj_from_dict
from mmdet import datasets
from mmdet.core import scatter, MMDataParallel, results2json, coco_eval
diff --git a/tools/train.py b/tools/train.py
index 03c87cc..41b66f3 100644
--- a/tools/train.py
+++ b/tools/train.py
@@ -7,7 +7,7 @@ from collections import OrderedDict
import numpy as np
import torch
from mmcv import Config
-from mmcv.torchpack import Runner, obj_from_dict
+from mmcv.runner import Runner, obj_from_dict
from mmdet import datasets, __version__
from mmdet.core import (init_dist, DistOptimizerHook, DistSamplerSeedHook,
--
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