Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[TL] ERROR: file models/pose.npz doesn't exist. #152

Closed
zeppafi opened this issue Nov 6, 2018 · 6 comments
Closed

[TL] ERROR: file models/pose.npz doesn't exist. #152

zeppafi opened this issue Nov 6, 2018 · 6 comments

Comments

@zeppafi
Copy link

zeppafi commented Nov 6, 2018 •
edited

Hi,

Thanks for the awesome project!

I cloned the project and typed commands:

pip3 install -r requirements.txt
pip3 install pycocotools
python3 train.py

I tried to run last command for couple of times, but the same error seems to reoccur (see below).

I'm running this on Linux:
Linux version 4.15.0-38-generic (buildd@lcy01-amd64-023) (gcc version 7.3.0 (Ubuntu 7.3.0-16ubuntu3)) #41-Ubuntu SMP Wed Oct 10 10:59:38 UTC 2018

~/openpose-plus$ python3 train.py
[TL] annotations exists
[TL] validating images exists
[TL] training images exists
[TL] testing images exists
[x] Get pose data from data/mscoco2017/train2017
loading annotations into memory...
Done (t=11.38s)
creating index...
index created!
Overall get 56599 valid pose images from data/mscoco2017/train2017 and data/mscoco2017/annotations/person_keypoints_train2017.json
data/mscoco2017/train2017 has 56599 images
[x] Get pose data from data/mscoco2017/val2017
loading annotations into memory...
Done (t=0.24s)
creating index...
index created!
Overall get 2346 valid pose images from data/mscoco2017/val2017 and data/mscoco2017/annotations/person_keypoints_val2017.json
data/mscoco2017/val2017 has 2346 images
[TL] InputLayer model/input: (?, 368, 368, 3)
[TL] Conv2d model/conv1_1: n_filter: 64 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/conv1_2: n_filter: 64 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] MaxPool2d model/pool1: filter_size: (2, 2) strides: (2, 2) padding: SAME
[TL] Conv2d model/conv2_1: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/conv2_2: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] MaxPool2d model/pool2: filter_size: (2, 2) strides: (2, 2) padding: SAME
[TL] Conv2d model/conv3_1: n_filter: 256 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/conv3_2: n_filter: 256 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/conv3_3: n_filter: 256 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/conv3_4: n_filter: 256 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] MaxPool2d model/pool3: filter_size: (2, 2) strides: (2, 2) padding: SAME
[TL] Conv2d model/conv4_1: n_filter: 512 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/conv4_2: n_filter: 512 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/conv4_3: n_filter: 256 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/conv4_4: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage1/branch1/c1: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage1/branch1/c2: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage1/branch1/c3: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage1/branch1/c4: n_filter: 512 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage1/branch1/confs: n_filter: 19 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] Conv2d model/stage1/branch2/c1: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage1/branch2/c2: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage1/branch2/c3: n_filter: 128 filter_size: (3, 3) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage1/branch2/c4: n_filter: 512 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage1/branch2/pafs: n_filter: 38 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] ConcatLayer model/stage2/concat: axis: -1
[TL] Conv2d model/stage2/branch1/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch1/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch1/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch1/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch1/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch1/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage2/branch1/conf: n_filter: 19 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] Conv2d model/stage2/branch2/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch2/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch2/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch2/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch2/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage2/branch2/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage2/branch2/pafs: n_filter: 38 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] ConcatLayer model/stage3/concat: axis: -1
[TL] Conv2d model/stage3/branch1/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch1/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch1/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch1/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch1/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch1/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage3/branch1/conf: n_filter: 19 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] Conv2d model/stage3/branch2/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch2/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch2/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch2/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch2/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage3/branch2/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage3/branch2/pafs: n_filter: 38 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] ConcatLayer model/stage4/concat: axis: -1
[TL] Conv2d model/stage4/branch1/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch1/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch1/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch1/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch1/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch1/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage4/branch1/conf: n_filter: 19 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] Conv2d model/stage4/branch2/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch2/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch2/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch2/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch2/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage4/branch2/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage4/branch2/pafs: n_filter: 38 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] ConcatLayer model/stage5/concat: axis: -1
[TL] Conv2d model/stage5/branch1/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch1/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch1/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch1/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch1/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch1/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage5/branch1/conf: n_filter: 19 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] Conv2d model/stage5/branch2/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch2/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch2/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch2/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch2/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage5/branch2/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage5/branch2/pafs: n_filter: 38 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] ConcatLayer model/stage6/concat: axis: -1
[TL] Conv2d model/stage6/branch1/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch1/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch1/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch1/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch1/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch1/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage6/branch1/conf: n_filter: 19 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] Conv2d model/stage6/branch2/c1: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch2/c2: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch2/c3: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch2/c4: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch2/c5: n_filter: 128 filter_size: (7, 7) strides: (1, 1) pad: SAME act: relu
[TL] Conv2d model/stage6/branch2/c6: n_filter: 128 filter_size: (1, 1) strides: (1, 1) pad: VALID act: relu
[TL] Conv2d model/stage6/branch2/pafs: n_filter: 38 filter_size: (1, 1) strides: (1, 1) pad: VALID act: No Activation
[TL] [*] geting variables with kernel
[TL] got 0: model/conv1_1/kernel:0 (3, 3, 3, 64)
[TL] got 1: model/conv1_2/kernel:0 (3, 3, 64, 64)
[TL] got 2: model/conv2_1/kernel:0 (3, 3, 64, 128)
[TL] got 3: model/conv2_2/kernel:0 (3, 3, 128, 128)
[TL] got 4: model/conv3_1/kernel:0 (3, 3, 128, 256)
[TL] got 5: model/conv3_2/kernel:0 (3, 3, 256, 256)
[TL] got 6: model/conv3_3/kernel:0 (3, 3, 256, 256)
[TL] got 7: model/conv3_4/kernel:0 (3, 3, 256, 256)
[TL] got 8: model/conv4_1/kernel:0 (3, 3, 256, 512)
[TL] got 9: model/conv4_2/kernel:0 (3, 3, 512, 512)
[TL] got 10: model/conv4_3/kernel:0 (3, 3, 512, 256)
[TL] got 11: model/conv4_4/kernel:0 (3, 3, 256, 128)
[TL] got 12: model/stage1/branch1/c1/kernel:0 (3, 3, 128, 128)
[TL] got 13: model/stage1/branch1/c2/kernel:0 (3, 3, 128, 128)
[TL] got 14: model/stage1/branch1/c3/kernel:0 (3, 3, 128, 128)
[TL] got 15: model/stage1/branch1/c4/kernel:0 (1, 1, 128, 512)
[TL] got 16: model/stage1/branch1/confs/kernel:0 (1, 1, 512, 19)
[TL] got 17: model/stage1/branch2/c1/kernel:0 (3, 3, 128, 128)
[TL] got 18: model/stage1/branch2/c2/kernel:0 (3, 3, 128, 128)
[TL] got 19: model/stage1/branch2/c3/kernel:0 (3, 3, 128, 128)
[TL] got 20: model/stage1/branch2/c4/kernel:0 (1, 1, 128, 512)
[TL] got 21: model/stage1/branch2/pafs/kernel:0 (1, 1, 512, 38)
[TL] got 22: model/stage2/branch1/c1/kernel:0 (7, 7, 185, 128)
[TL] got 23: model/stage2/branch1/c2/kernel:0 (7, 7, 128, 128)
[TL] got 24: model/stage2/branch1/c3/kernel:0 (7, 7, 128, 128)
[TL] got 25: model/stage2/branch1/c4/kernel:0 (7, 7, 128, 128)
[TL] got 26: model/stage2/branch1/c5/kernel:0 (7, 7, 128, 128)
[TL] got 27: model/stage2/branch1/c6/kernel:0 (1, 1, 128, 128)
[TL] got 28: model/stage2/branch1/conf/kernel:0 (1, 1, 128, 19)
[TL] got 29: model/stage2/branch2/c1/kernel:0 (7, 7, 185, 128)
[TL] got 30: model/stage2/branch2/c2/kernel:0 (7, 7, 128, 128)
[TL] got 31: model/stage2/branch2/c3/kernel:0 (7, 7, 128, 128)
[TL] got 32: model/stage2/branch2/c4/kernel:0 (7, 7, 128, 128)
[TL] got 33: model/stage2/branch2/c5/kernel:0 (7, 7, 128, 128)
[TL] got 34: model/stage2/branch2/c6/kernel:0 (1, 1, 128, 128)
[TL] got 35: model/stage2/branch2/pafs/kernel:0 (1, 1, 128, 38)
[TL] got 36: model/stage3/branch1/c1/kernel:0 (7, 7, 185, 128)
[TL] got 37: model/stage3/branch1/c2/kernel:0 (7, 7, 128, 128)
[TL] got 38: model/stage3/branch1/c3/kernel:0 (7, 7, 128, 128)
[TL] got 39: model/stage3/branch1/c4/kernel:0 (7, 7, 128, 128)
[TL] got 40: model/stage3/branch1/c5/kernel:0 (7, 7, 128, 128)
[TL] got 41: model/stage3/branch1/c6/kernel:0 (1, 1, 128, 128)
[TL] got 42: model/stage3/branch1/conf/kernel:0 (1, 1, 128, 19)
[TL] got 43: model/stage3/branch2/c1/kernel:0 (7, 7, 185, 128)
[TL] got 44: model/stage3/branch2/c2/kernel:0 (7, 7, 128, 128)
[TL] got 45: model/stage3/branch2/c3/kernel:0 (7, 7, 128, 128)
[TL] got 46: model/stage3/branch2/c4/kernel:0 (7, 7, 128, 128)
[TL] got 47: model/stage3/branch2/c5/kernel:0 (7, 7, 128, 128)
[TL] got 48: model/stage3/branch2/c6/kernel:0 (1, 1, 128, 128)
[TL] got 49: model/stage3/branch2/pafs/kernel:0 (1, 1, 128, 38)
[TL] got 50: model/stage4/branch1/c1/kernel:0 (7, 7, 185, 128)
[TL] got 51: model/stage4/branch1/c2/kernel:0 (7, 7, 128, 128)
[TL] got 52: model/stage4/branch1/c3/kernel:0 (7, 7, 128, 128)
[TL] got 53: model/stage4/branch1/c4/kernel:0 (7, 7, 128, 128)
[TL] got 54: model/stage4/branch1/c5/kernel:0 (7, 7, 128, 128)
[TL] got 55: model/stage4/branch1/c6/kernel:0 (1, 1, 128, 128)
[TL] got 56: model/stage4/branch1/conf/kernel:0 (1, 1, 128, 19)
[TL] got 57: model/stage4/branch2/c1/kernel:0 (7, 7, 185, 128)
[TL] got 58: model/stage4/branch2/c2/kernel:0 (7, 7, 128, 128)
[TL] got 59: model/stage4/branch2/c3/kernel:0 (7, 7, 128, 128)
[TL] got 60: model/stage4/branch2/c4/kernel:0 (7, 7, 128, 128)
[TL] got 61: model/stage4/branch2/c5/kernel:0 (7, 7, 128, 128)
[TL] got 62: model/stage4/branch2/c6/kernel:0 (1, 1, 128, 128)
[TL] got 63: model/stage4/branch2/pafs/kernel:0 (1, 1, 128, 38)
[TL] got 64: model/stage5/branch1/c1/kernel:0 (7, 7, 185, 128)
[TL] got 65: model/stage5/branch1/c2/kernel:0 (7, 7, 128, 128)
[TL] got 66: model/stage5/branch1/c3/kernel:0 (7, 7, 128, 128)
[TL] got 67: model/stage5/branch1/c4/kernel:0 (7, 7, 128, 128)
[TL] got 68: model/stage5/branch1/c5/kernel:0 (7, 7, 128, 128)
[TL] got 69: model/stage5/branch1/c6/kernel:0 (1, 1, 128, 128)
[TL] got 70: model/stage5/branch1/conf/kernel:0 (1, 1, 128, 19)
[TL] got 71: model/stage5/branch2/c1/kernel:0 (7, 7, 185, 128)
[TL] got 72: model/stage5/branch2/c2/kernel:0 (7, 7, 128, 128)
[TL] got 73: model/stage5/branch2/c3/kernel:0 (7, 7, 128, 128)
[TL] got 74: model/stage5/branch2/c4/kernel:0 (7, 7, 128, 128)
[TL] got 75: model/stage5/branch2/c5/kernel:0 (7, 7, 128, 128)
[TL] got 76: model/stage5/branch2/c6/kernel:0 (1, 1, 128, 128)
[TL] got 77: model/stage5/branch2/pafs/kernel:0 (1, 1, 128, 38)
[TL] got 78: model/stage6/branch1/c1/kernel:0 (7, 7, 185, 128)
[TL] got 79: model/stage6/branch1/c2/kernel:0 (7, 7, 128, 128)
[TL] got 80: model/stage6/branch1/c3/kernel:0 (7, 7, 128, 128)
[TL] got 81: model/stage6/branch1/c4/kernel:0 (7, 7, 128, 128)
[TL] got 82: model/stage6/branch1/c5/kernel:0 (7, 7, 128, 128)
[TL] got 83: model/stage6/branch1/c6/kernel:0 (1, 1, 128, 128)
[TL] got 84: model/stage6/branch1/conf/kernel:0 (1, 1, 128, 19)
[TL] got 85: model/stage6/branch2/c1/kernel:0 (7, 7, 185, 128)
[TL] got 86: model/stage6/branch2/c2/kernel:0 (7, 7, 128, 128)
[TL] got 87: model/stage6/branch2/c3/kernel:0 (7, 7, 128, 128)
[TL] got 88: model/stage6/branch2/c4/kernel:0 (7, 7, 128, 128)
[TL] got 89: model/stage6/branch2/c5/kernel:0 (7, 7, 128, 128)
[TL] got 90: model/stage6/branch2/c6/kernel:0 (1, 1, 128, 128)
[TL] got 91: model/stage6/branch2/pafs/kernel:0 (1, 1, 128, 38)
Start - n_step: 600000 batch_size: 8 lr_init: 4e-05 lr_decay_every_step: 136106
[TL] ERROR: file models/pose.npz doesn't exist.
2018-11-06 15:19:34.013385: W tensorflow/core/framework/op_kernel.cc:1261] Invalid argument: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

2018-11-06 15:19:34.013388: W tensorflow/core/framework/op_kernel.cc:1261] Invalid argument: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

2018-11-06 15:19:34.013904: W tensorflow/core/framework/op_kernel.cc:1261] Invalid argument: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

2018-11-06 15:19:34.014117: W tensorflow/core/framework/op_kernel.cc:1261] Invalid argument: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

2018-11-06 15:19:34.030183: W tensorflow/core/framework/op_kernel.cc:1261] Invalid argument: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

2018-11-06 15:19:34.037101: W tensorflow/core/framework/op_kernel.cc:1261] Invalid argument: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

2018-11-06 15:19:34.037555: W tensorflow/core/framework/op_kernel.cc:1261] Invalid argument: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

Traceback (most recent call last):
File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1334, in _do_call
return fn(*args)
File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

 [[{{node PyFunc}} = PyFunc[Tin=[DT_FLOAT, DT_STRING], Tout=[DT_FLOAT, DT_FLOAT, DT_FLOAT], token="pyfunc_3"](convert_image, arg1)]]
 [[{{node IteratorGetNext}} = IteratorGetNext[output_shapes=[[?,368,368,3], [?,46,46,57], [?,46,46,1]], output_types=[DT_FLOAT, DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](OneShotIterator)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 471, in
single_train(dataset)
File "train.py", line 255, in single_train
sess.run([train_op, total_loss, stage_losses, l2_loss, last_conf, last_paf])
File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 929, in run
run_metadata_ptr)
File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1328, in _do_run
run_metadata)
File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'
Traceback (most recent call last):

File "/home/jaakko/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 206, in call
ret = func(*args)

File "train.py", line 154, in _data_aug_fn
mask_miss = tl.prepro.affine_transform_cv2(mask_miss, transform_matrix, border_mode='replicate')

TypeError: affine_transform_cv2() got an unexpected keyword argument 'border_mode'

 [[{{node PyFunc}} = PyFunc[Tin=[DT_FLOAT, DT_STRING], Tout=[DT_FLOAT, DT_FLOAT, DT_FLOAT], token="pyfunc_3"](convert_image, arg1)]]
 [[node IteratorGetNext (defined at train.py:212)  = IteratorGetNext[output_shapes=[[?,368,368,3], [?,46,46,57], [?,46,46,1]], output_types=[DT_FLOAT, DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](OneShotIterator)]]
@Jerry3062
Copy link

I met the same problem yet.

@luomai
Copy link
Member

luomai commented Nov 7, 2018 •
edited

You would need to install the TensorLayer on the master branch as the augmentation is using a new API that is not available on the stable release.

Here is the related commit: PR 885

@zeppafi
Copy link
Author

zeppafi commented Nov 7, 2018

Thanks, I was able to proceed.

I had to run pip3 uninstall tensorlayer. After pip3 show tensorlayer didn't show anything, I typed pip3 install https://github.com/tensorlayer/tensorlayer/archive/master.zip (as documented on tensorlayer readme) and tested again with python3 train.py.

Now script proceeds to training phase even thought "[TL] ERROR: file models/pose.npz doesn't exist." is still printed.

@luomai
Copy link
Member

luomai commented Nov 7, 2018

This error is expected and your training is just fine. This is because the training program always try to read an existing npz file to recover from a checkpoint.

I will make a commit to remove this default reading behaviour.

@luomai
Copy link
Member

luomai commented Nov 15, 2018

Hello @zeppafi , the new API has been released in TL 1.11.1. So you don't need to install from the master head anymore. Feel free to reopen this issue if you have any further question. :)

@luomai luomai closed this as completed Nov 15, 2018
@yaelRsip
Copy link

Updating Tensorlayer, uninstalling and reinstalling tensorlayer using:
pip install tensorlayer,
pip3 install tensorlayer and pip3 install tensorlayer-1.11.1-py2.py3-none-any.whl

All these, when checking tensorlayer's version in python:

import tensorlayer
tensorlayer.__version__

result in tensorlayer 11.1.0 .

And result with the same error mentioned above when running python train.py

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
4 participants
@luomai @Jerry3062 @zeppafi @yaelRsip