YangZeyu95
commented
5 years ago Which version of tensorflow you are using? Main is 1.12
Open bardia-esm opened 5 years ago
YangZeyu95
commented
5 years ago Which version of tensorflow you are using? Main is 1.12
YangZeyu95
commented
5 years ago And there is a '/' missing at the end of '--checkpoints_path' para in line25
bardia-esm
commented
5 years ago My tensorflow version is 1.14 As you mentioned I added a '/' to the end of the checkpoint path and now I get the following error
WARNING: Logging before flag parsing goes to stderr.
I0713 22:02:50.059869 140150081058624 run.py:37] checkpoint_path: checkpoints/pretrained/
W0713 22:02:50.060944 140150081058624 deprecation_wrapper.py:119] From run.py:40: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
W0713 22:02:50.066842 140150081058624 deprecation_wrapper.py:119] From /home/bardia/Documents/University/Bachelor Project/unofficial-implement-of-openpose/vgg.py:244: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
[2019-07-13 22:02:51,052] [run] [INFO] initializing model...
I0713 22:02:51.052708 140150081058624 run.py:50] initializing model...
W0713 22:02:51.061728 140150081058624 deprecation_wrapper.py:119] From /home/bardia/Documents/University/Bachelor Project/unofficial-implement-of-openpose/cpm.py:141: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
W0713 22:02:51.114830 140150081058624 deprecation_wrapper.py:119] From /home/bardia/Documents/University/Bachelor Project/unofficial-implement-of-openpose/cpm.py:153: The name tf.summary.histogram is deprecated. Please use tf.compat.v1.summary.histogram instead.
W0713 22:02:54.495259 140150081058624 deprecation_wrapper.py:119] From run.py:54: The name tf.image.resize_area is deprecated. Please use tf.compat.v1.image.resize_area instead.
W0713 22:02:54.516101 140150081058624 deprecation.py:323] From run.py:63: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
[2019-07-13 22:02:54,516] [run] [INFO] initialize saver...
I0713 22:02:54.516945 140150081058624 run.py:65] initialize saver...
W0713 22:02:54.517126 140150081058624 deprecation_wrapper.py:119] From run.py:68: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
W0713 22:02:54.517249 140150081058624 deprecation_wrapper.py:119] From run.py:68: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.
W0713 22:02:54.518206 140150081058624 deprecation_wrapper.py:119] From run.py:72: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.
[2019-07-13 22:02:54,865] [run] [INFO] initialize session...
I0713 22:02:54.865621 140150081058624 run.py:74] initialize session...
2019-07-13 22:02:54.866032: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-07-13 22:02:54.892454: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2494300000 Hz
2019-07-13 22:02:54.892873: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x6131360 executing computations on platform Host. Devices:
2019-07-13 22:02:54.892909: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): <undefined>, <undefined>
2019-07-13 22:02:55.710225: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1412] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set. If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU. To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.
2019-07-13 22:02:55.805702: W tensorflow/core/framework/allocator.cc:107] Allocation of 411041792 exceeds 10% of system memory.
[2019-07-13 22:02:56,638] [run] [INFO] restoring vgg weights...
I0713 22:02:56.638266 140150081058624 run.py:79] restoring vgg weights...
W0713 22:02:56.638562 140150081058624 deprecation.py:323] From /home/bardia/env_dir/main_venv/lib/python3.6/site-packages/tensorflow/python/training/saver.py:1276: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.
Instructions for updating:
Use standard file APIs to check for files with this prefix.
2019-07-13 22:02:56.948333: W tensorflow/core/framework/allocator.cc:107] Allocation of 411041792 exceeds 10% of system memory.
[2019-07-13 22:02:59,409] [run] [INFO] restoring from checkpoint...
I0713 22:02:59.409865 140150081058624 run.py:81] restoring from checkpoint...
2019-07-13 22:02:59.842244: W tensorflow/core/framework/allocator.cc:107] Allocation of 411041792 exceeds 10% of system memory.
[2019-07-13 22:03:01,497] [run] [INFO] initialization done
I0713 22:03:01.497821 140150081058624 run.py:84] initialization done
[tcp @ 0x73d5880] Connection to tcp://192.168.1.52:8081 failed: No route to host
[2019-07-13 22:03:04,768] [run] [ERROR] Can't read video
E0713 22:03:04.768429 140150081058624 run.py:93] Can't read videoThat error means can't read the video, check your video path.
Hi
I am trying to use run.py with webcam on a cpu-only machine
I downloaded the vgg19 and pretrained models and made checkpoints directory as bellow:
and changed the code like this:
however when I execute run.py , I get the following error:
should I change any part of the code, since I have a cpu-only machine like line 76 in run.py? could you help me where I am doing wrong?