Open spy78111 opened 4 years ago
RetinaFace使用InsightFace的retianface训练，mxnet环境，主干模型选择resnet-50,得到训练模型后需要转换为caffe模型，在mxnet2caffe时遇到如下错误: .. .. .. 24 | face_rpn_cls_score_stride8_weight -> face_rpn_cls_score_stride8 , initialized. face_rpn_landmark_pred_stride16_bias: (20,)->(20, 256, 1, 1) 25 | face_rpn_landmark_pred_stride16_bias -> face_rpn_landmark_pred_stride16, initialized. ('face_rpn_landmark_pred_stride16_weight', 'face_rpn_landmark_pred_stride16') face_rpn_landmark_pred_stride16_weight: (20, 256, 1, 1)->(20, 256, 1, 1) 26 | face_rpn_landmark_pred_stride16_weight -> face_rpn_landmark_pred_stride16, initialized. face_rpn_landmark_pred_stride32_bias: (20,)->(20, 256, 1, 1) 27 | face_rpn_landmark_pred_stride32_bias -> face_rpn_landmark_pred_stride32, initialized. ('face_rpn_landmark_pred_stride32_weight', 'face_rpn_landmark_pred_stride32') face_rpn_landmark_pred_stride32_weight: (20, 256, 1, 1)->(20, 256, 1, 1) 28 | face_rpn_landmark_pred_stride32_weight -> face_rpn_landmark_pred_stride32, initialized. face_rpn_landmark_pred_stride8_bias: (20,)->(20, 256, 1, 1) 29 | face_rpn_landmark_pred_stride8_bias -> face_rpn_landmark_pred_stride8, initialized. ('face_rpn_landmark_pred_stride8_weight', 'face_rpn_landmark_pred_stride8') face_rpn_landmark_pred_stride8_weight: (20, 256, 1, 1)->(20, 256, 1, 1) 30 | face_rpn_landmark_pred_stride8_weight -> face_rpn_landmark_pred_stride8, initialized. rf_c1_aggr_bias: (256,)->(256, 256, 3, 3) 31 | rf_c1_aggr_bias -> rf_c1_aggr , initialized. ('key in mxnet', 'rf_c1_aggr_bn_beta', True) ('key in caffe', 'rf_c1_aggr_bn_fwd_scale', False) Traceback (most recent call last): File "mxnet2caffe.py", line 108, in print("{}: {}->{}".format(key_i, arg_params[key_i].shape, net.params[key_caffe][0].data.shape)) KeyError: 'rf_c1_aggr_bn_fwd_scale' [root@TServer advanced-mxnet2caffe-master]# ('key in mxnet', 'rf_c1_aggr_bn_beta', True) ('key in caffe', 'rf_c1_aggr_bn_fwd_scale', False) Traceback (most recent call last): File "mxnet2caffe.py", line 108, in print("{}: {}->{}".format(key_i, arg_params[key_i].shape, net.params[key_caffe][0].data.shape)) KeyError: 'rf_c1_aggr_bn_fwd_scale' bash: key in mxnet,: 未找到命令...
麻烦哪位大佬帮看下什么问题，不慎感谢
RetinaFace使用InsightFace的retianface训练，mxnet环境，主干模型选择resnet-50,得到训练模型后需要转换为caffe模型，在mxnet2caffe时遇到如下错误: .. .. .. 24 | face_rpn_cls_score_stride8_weight -> face_rpn_cls_score_stride8 , initialized. face_rpn_landmark_pred_stride16_bias: (20,)->(20, 256, 1, 1) 25 | face_rpn_landmark_pred_stride16_bias -> face_rpn_landmark_pred_stride16, initialized. ('face_rpn_landmark_pred_stride16_weight', 'face_rpn_landmark_pred_stride16') face_rpn_landmark_pred_stride16_weight: (20, 256, 1, 1)->(20, 256, 1, 1) 26 | face_rpn_landmark_pred_stride16_weight -> face_rpn_landmark_pred_stride16, initialized. face_rpn_landmark_pred_stride32_bias: (20,)->(20, 256, 1, 1) 27 | face_rpn_landmark_pred_stride32_bias -> face_rpn_landmark_pred_stride32, initialized. ('face_rpn_landmark_pred_stride32_weight', 'face_rpn_landmark_pred_stride32') face_rpn_landmark_pred_stride32_weight: (20, 256, 1, 1)->(20, 256, 1, 1) 28 | face_rpn_landmark_pred_stride32_weight -> face_rpn_landmark_pred_stride32, initialized. face_rpn_landmark_pred_stride8_bias: (20,)->(20, 256, 1, 1) 29 | face_rpn_landmark_pred_stride8_bias -> face_rpn_landmark_pred_stride8, initialized. ('face_rpn_landmark_pred_stride8_weight', 'face_rpn_landmark_pred_stride8') face_rpn_landmark_pred_stride8_weight: (20, 256, 1, 1)->(20, 256, 1, 1) 30 | face_rpn_landmark_pred_stride8_weight -> face_rpn_landmark_pred_stride8, initialized. rf_c1_aggr_bias: (256,)->(256, 256, 3, 3) 31 | rf_c1_aggr_bias -> rf_c1_aggr , initialized. ('key in mxnet', 'rf_c1_aggr_bn_beta', True) ('key in caffe', 'rf_c1_aggr_bn_fwd_scale', False) Traceback (most recent call last): File "mxnet2caffe.py", line 108, in
print("{}: {}->{}".format(key_i, arg_params[key_i].shape, net.params[key_caffe][0].data.shape))
KeyError: 'rf_c1_aggr_bn_fwd_scale'
[root@TServer advanced-mxnet2caffe-master]# ('key in mxnet', 'rf_c1_aggr_bn_beta', True)
('key in caffe', 'rf_c1_aggr_bn_fwd_scale', False)
Traceback (most recent call last):
File "mxnet2caffe.py", line 108, in
print("{}: {}->{}".format(key_i, arg_params[key_i].shape, net.params[key_caffe][0].data.shape))
KeyError: 'rf_c1_aggr_bn_fwd_scale'
bash: key in mxnet,: 未找到命令...
麻烦哪位大佬帮看下什么问题，不慎感谢