NotFoundError Traceback (most recent call last)

in ()
1
----> 2 deeplabcut.train_network(path_config_file, shuffle=1, displayiters=10,saveiters=500)
3
4 #this will run until you stop it (CTRL+C), or hit "STOP" icon, or when it hits the end (default, 1.03M iterations).
5 #Whichever you chose, you will see what looks like an error message, but it's not an error - don't worry....

/usr/local/lib/python3.6/dist-packages/deeplabcut/pose_estimation_tensorflow/training.py in train_network(config, shuffle, trainingsetindex, gputouse, max_snapshots_to_keep, autotune, displayiters, saveiters, maxiters)
79 train(str(poseconfigfile),displayiters,saveiters,maxiters,max_to_keep=max_snapshots_to_keep) #pass on path and file name for pose_cfg.yaml!
80 except BaseException as e:
---> 81 raise e
82 finally:
83 os.chdir(str(start_path))

/usr/local/lib/python3.6/dist-packages/deeplabcut/pose_estimation_tensorflow/training.py in train_network(config, shuffle, trainingsetindex, gputouse, max_snapshots_to_keep, autotune, displayiters, saveiters, maxiters)
77 os.environ['CUDA_VISIBLE_DEVICES'] = str(gputouse)
78 try:
---> 79 train(str(poseconfigfile),displayiters,saveiters,maxiters,max_to_keep=max_snapshots_to_keep) #pass on path and file name for pose_cfg.yaml!
80 except BaseException as e:
81 raise e

/usr/local/lib/python3.6/dist-packages/deeplabcut/pose_estimation_tensorflow/train.py in train(config_yaml, displayiters, saveiters, maxiters, max_to_keep)
107
108 # Restore variables from disk.
--> 109 restorer.restore(sess, cfg.init_weights)
110 if maxiters==None:
111 max_iter = int(cfg.multi_step[-1][1])

/usr/local/lib/python3.6/dist-packages/tensorflow/python/training/saver.py in restore(self, sess, save_path)
1534 raise ValueError("Can't load save_path when it is None.")
1535
-> 1536 if not checkpoint_management.checkpoint_exists(compat.as_text(save_path)):
1537 raise ValueError("The passed save_path is not a valid checkpoint: "
1538 + compat.as_text(save_path))

/usr/local/lib/python3.6/dist-packages/tensorflow/python/training/checkpoint_management.py in checkpoint_exists(checkpoint_prefix)
362 pathname = _prefix_to_checkpoint_path(checkpoint_prefix,
363 saver_pb2.SaverDef.V2)
--> 364 if file_io.get_matching_files(pathname):
365 return True
366 elif file_io.get_matching_files(checkpoint_prefix):

/usr/local/lib/python3.6/dist-packages/tensorflow/python/lib/io/file_io.py in get_matching_files(filename)
340 # Convert the filenames to string from bytes.
341 compat.as_str_any(matching_filename)
--> 342 for single_filename in filename
343 for matching_filename in pywrap_tensorflow.GetMatchingFiles(
344 compat.as_bytes(single_filename), status)

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/errors_impl.py in exit(self, type_arg, value_arg, traceback_arg)
526 None, None,
527 compat.as_text(c_api.TF_Message(self.status.status)),
--> 528 c_api.TF_GetCode(self.status.status))
529 # Delete the underlying status object from memory otherwise it stays alive
530 # as there is a reference to status from this from the traceback due to

NotFoundError: /content/drive/My Drive/DLC/lib/site-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained; No such file or directory

We had the same error.
FileNotFoundError: [Errno 2] No such file or directory: '/content/drive/My Drive/DLC/ThoroughbredDLC-Byron-2018-12-08/labeled-data\Sample34\img077.png'

I suppose you are using a windows computer to label the video. Notice the mix of forward and backward slashes in the image path. Colab seems to be running on linux.

A temporary solution that worked for us was to edit the labeling_toolbox.py file. After line
227: self.index = glob.glob(os.path.join(self.dir,'*.png'))
add a line that replaces the windows-style backslashes to forward slashes:
self.index = [ s.replace("\\", "/" for s in self.index ]
I did not check if this still works in windows, so it probably isn't a general solution, but the generated project was good in colab

Ah, simple fix to change the paths to Linux style, we have helper code for this; will put up on DLCUtils

Thanks.

I was actually looking at the bottom error "NotFoundError: /content/drive/My Drive/DLC/lib/site-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained; No such file or directory" and missed the "/" error.

Let me know when it is up in DLCUtils.

I put a quick fix on https://github.com/AlexEMG/DLCutils, see https://github.com/AlexEMG/DLCutils#running-project-created-on-windows-on-colaboratory

We will integrate this functionality in the next release of DLC (in an expanded way). Let me know if it works & makes sense!

Hi!

I believe I am still experiencing this issue.
I labelled the frames on a Windows PC (DLC version 2.1.6) and I am now on Colab (DLC version 2.1.7.1). During the 'create training dataset' step I get this:

FileNotFoundError: No such file: '/content/drive/My Drive/LP_Task_Nov19-Margarida-2020-04-03/labeled-data\LV_M8_S14\img29277.png'

Since the newer versions of DLC already fix for this issue, is there anything that I am doing wrong? How can I fix this?

Thank you!

you can covert your files to linux style first, but it should convert when you run create_training_dataset; can you put the full code you ran and output here?

Code:

deeplabcut.create_training_dataset(path_config_file, net_type='resnet_50', augmenter_type='imgaug')

Ouput:

FileNotFoundError                         Traceback (most recent call last)
<ipython-input-81-d43c96cb30c9> in <module>()
----> 1 deeplabcut.create_training_dataset(path_config_file, net_type='resnet_50', augmenter_type='imgaug')

9 frames
/usr/local/lib/python3.6/dist-packages/deeplabcut/generate_training_dataset/trainingsetmanipulation.py in create_training_dataset(config, num_shuffles, Shuffles, windows2linux, userfeedback, trainIndexes, testIndexes, net_type, augmenter_type)
    690             # Saving data file (convert to training file for deeper cut (*.mat))
    691             ################################################################################
--> 692             data, MatlabData = format_training_data(Data, trainIndexes, nbodyparts, project_path)
    693             sio.savemat(os.path.join(project_path,datafilename), {'dataset': MatlabData})
    694 

/usr/local/lib/python3.6/dist-packages/deeplabcut/generate_training_dataset/trainingsetmanipulation.py in format_training_data(df, train_inds, nbodyparts, project_path)
    546         filename = df.index[i]
    547         data['image'] = filename
--> 548         img_shape = _read_image_shape_fast(os.path.join(project_path, filename))
    549         try:
    550             data['size'] = img_shape[2], img_shape[0], img_shape[1]

/usr/local/lib/python3.6/dist-packages/deeplabcut/generate_training_dataset/trainingsetmanipulation.py in _read_image_shape_fast(path)
    531 @lru_cache(maxsize=None)
    532 def _read_image_shape_fast(path):
--> 533     return io.imread(path).shape
    534 
    535 def format_training_data(df, train_inds, nbodyparts, project_path):

/usr/local/lib/python3.6/dist-packages/skimage/io/_io.py in imread(fname, as_gray, plugin, **plugin_args)
     46 
     47     with file_or_url_context(fname) as fname:
---> 48         img = call_plugin('imread', fname, plugin=plugin, **plugin_args)
     49 
     50     if not hasattr(img, 'ndim'):

/usr/local/lib/python3.6/dist-packages/skimage/io/manage_plugins.py in call_plugin(kind, *args, **kwargs)
    208                                (plugin, kind))
    209 
--> 210     return func(*args, **kwargs)
    211 
    212 

/usr/local/lib/python3.6/dist-packages/skimage/io/_plugins/imageio_plugin.py in imread(*args, **kwargs)
      8 @wraps(imageio_imread)
      9 def imread(*args, **kwargs):
---> 10     return np.asarray(imageio_imread(*args, **kwargs))

/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py in imread(uri, format, **kwargs)
    219 
    220     # Get reader and read first
--> 221     reader = read(uri, format, "i", **kwargs)
    222     with reader:
    223         return reader.get_data(0)

/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py in get_reader(uri, format, mode, **kwargs)
    128 
    129     # Create request object
--> 130     request = Request(uri, "r" + mode, **kwargs)
    131 
    132     # Get format

/usr/local/lib/python3.6/dist-packages/imageio/core/request.py in __init__(self, uri, mode, **kwargs)
    123 
    124         # Parse what was given
--> 125         self._parse_uri(uri)
    126 
    127         # Set extension

/usr/local/lib/python3.6/dist-packages/imageio/core/request.py in _parse_uri(self, uri)
    271                 # Reading: check that the file exists (but is allowed a dir)
    272                 if not os.path.exists(fn):
--> 273                     raise FileNotFoundError("No such file: '%s'" % fn)
    274             else:
    275                 # Writing: check that the directory to write to does exist

FileNotFoundError: No such file: '/content/drive/My Drive/LP_Task_Nov19-Margarida-2020-04-03/labeled-data\LV_M12_S14\img017712.png'

can you also pass windows2linux=True when you run that call

i.e.

deeplabcut.create_training_dataset(path_config_file, net_type='resnet_50', augmenter_type='imgaug', windows2linux=True)

It solved the issue!
Thanks a lot for your help.