Open chuong opened 3 years ago
@okankop: load pretrain model does not require loading backbones. However skipping backbone arguments causes error:
$ python train.py --dataset ucf101-24 --data_cfg cfg/ucf24.data --cfg_file cfg/ucf24.cfg --n_classes 24 --resume_path weights/yowo_ucf101-24_16f_best.pth --evaluate
Traceback (most recent call last):
File "train.py", line 89, in <module>
model = YOWO(opt)
File "/repos/YOWO/model.py", line 29, in __init__
it from [darknet]")
ValueError: Wrong backbone_2d model is requested. Please select it from [darknet]
If I keep all the arguments and provide all pretrained models, evaluation produces results of zeros:
$ python train.py --dataset ucf101-24 --data_cfg cfg/ucf24.data --cfg_file cfg/ucf24.cfg --n_classes 24 --backbone_3d resnext101 --backbone_3d_weights weights/resnext-101-kinetics.pth --backbone_2d darknet --backbone_2d_weights weights/yolo.weights --resume_path weights/yowo_ucf101-24_16f_best.pth --evaluate
DataParallel(
(module): YOWO(
(backbone_2d): Darknet(
..........................
(conv_final): Conv2d(1024, 145, kernel_size=(1, 1), stride=(1, 1), bias=False)
)
)
===================================================================
loading checkpoint weights/yowo_ucf101-24_16f_best.pth
Loaded model fscore: 0.9151895290027773
===================================================================
2020-09-30 00:25:33 evaluating ...
2020-09-30 00:25:34 validation at epoch 0
/repos/YOWO/utils.py:280: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.
cls_confs = torch.nn.Softmax()(Variable(output[5:5+num_classes].transpose(0,1))).data
2020-09-30 00:25:42 [0/22926] precision: 0.000000, recall: 0.000000, fscore: 0.000000
2020-09-30 00:25:42 [1/22926] precision: 0.000000, recall: 0.000000, fscore: 0.000000
2020-09-30 00:25:43 [2/22926] precision: 0.000000, recall: 0.000000, fscore: 0.000000
..............................................
Please help with this.
@chuong
I ran
python train.py --dataset ucf101-24 --data_cfg cfg/ucf24.data --cfg_file cfg/ucf24.cfg --n_classes 24 --backbone_3d resnext101 --backbone_3d_weights weights/resnext-101-kinetics.pth --backbone_2d darknet --resume_path weights/yowo_ucf101-24_16f_best.pth --evaluate
The first a few lines gave all 0, but after that non-zero results showed up:
2020-11-10 13:15:11 [313/11463] precision: 0.741367, recall: 0.776899, fscore: 0.758713 2020-11-10 13:15:11 [314/11463] precision: 0.742075, recall: 0.777539, fscore: 0.759388 2020-11-10 13:15:12 [315/11463] precision: 0.742779, recall: 0.778175, fscore: 0.760060 2020-11-10 13:15:12 [316/11463] precision: 0.743479, recall: 0.778807, fscore: 0.760728 2020-11-10 13:15:13 [317/11463] precision: 0.744176, recall: 0.779436, fscore: 0.761393 2020-11-10 13:15:14 [318/11463] precision: 0.744868, recall: 0.780061, fscore: 0.762054
@okankop: load pretrain model does not require loading backbones. However skipping backbone arguments causes error:
$ python train.py --dataset ucf101-24 --data_cfg cfg/ucf24.data --cfg_file cfg/ucf24.cfg --n_classes 24 --resume_path weights/yowo_ucf101-24_16f_best.pth --evaluate Traceback (most recent call last): File "train.py", line 89, in <module> model = YOWO(opt) File "/repos/YOWO/model.py", line 29, in __init__ it from [darknet]") ValueError: Wrong backbone_2d model is requested. Please select it from [darknet]
If I keep all the arguments and provide all pretrained models, evaluation produces results of zeros:
$ python train.py --dataset ucf101-24 --data_cfg cfg/ucf24.data --cfg_file cfg/ucf24.cfg --n_classes 24 --backbone_3d resnext101 --backbone_3d_weights weights/resnext-101-kinetics.pth --backbone_2d darknet --backbone_2d_weights weights/yolo.weights --resume_path weights/yowo_ucf101-24_16f_best.pth --evaluate DataParallel( (module): YOWO( (backbone_2d): Darknet( .......................... (conv_final): Conv2d(1024, 145, kernel_size=(1, 1), stride=(1, 1), bias=False) ) ) =================================================================== loading checkpoint weights/yowo_ucf101-24_16f_best.pth Loaded model fscore: 0.9151895290027773 =================================================================== 2020-09-30 00:25:33 evaluating ... 2020-09-30 00:25:34 validation at epoch 0 /repos/YOWO/utils.py:280: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument. cls_confs = torch.nn.Softmax()(Variable(output[5:5+num_classes].transpose(0,1))).data 2020-09-30 00:25:42 [0/22926] precision: 0.000000, recall: 0.000000, fscore: 0.000000 2020-09-30 00:25:42 [1/22926] precision: 0.000000, recall: 0.000000, fscore: 0.000000 2020-09-30 00:25:43 [2/22926] precision: 0.000000, recall: 0.000000, fscore: 0.000000 ..............................................
Please help with this. I also meet this fucking problem,how can i solve it
@chuong @C-popKingJames Any one solved this problem?
No, I also wanna to find this problem
@abhigoku10
Originally posted by @okankop in https://github.com/wei-tim/YOWO/issues/11#issuecomment-591884260