@@ -1,4 +1,6 @@
 _base_ = '../fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
+img_norm_cfg = dict(
+    mean=[103.53, 116.28, 123.675], std=[57.375, 57.12, 58.395], to_rgb=False)
 model = dict(
     pretrained='open-mmlab://msra/hrnetv2_w32',
     backbone=dict(
_base_ = '../fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
model = dict(
    pretrained='open-mmlab://msra/hrnetv2_w32',
    backbone=dict(
        _delete_=True,
        type='HRNet',
        extra=dict(
            stage1=dict(
                num_modules=1,
                num_branches=1,
                block='BOTTLENECK',
                num_blocks=(4, ),
                num_channels=(64, )),
            stage2=dict(
                num_modules=1,
                num_branches=2,
                block='BASIC',
                num_blocks=(4, 4),
                num_channels=(32, 64)),
            stage3=dict(
                num_modules=4,
                num_branches=3,
                block='BASIC',
                num_blocks=(4, 4, 4),
                num_channels=(32, 64, 128)),
            stage4=dict(
                num_modules=3,
                num_branches=4,
                block='BASIC',
                num_blocks=(4, 4, 4, 4),
                num_channels=(32, 64, 128, 256)))),
    neck=dict(
        _delete_=True,
        type='HRFPN',
        in_channels=[32, 64, 128, 256],
        out_channels=256,
        stride=2,
        num_outs=5))

This will not change the real img_norm_cfg used during training and testing because img_norm_cfg here is an intermediate variable, if you modify img_norm_cfg, you should also modify `train_pipeline` and `test_pipeline`. See configs/hrnet/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco.py