Fix of windows compatibility issues

- binary files need to be opened with 'rb' or 'wb' flag
- leveldb package is not available for windows - display warning instead of crashing
- adapted find_executable with fallback for windows ".exe" extension and let the version check pass
- normalization of path separators to linux style
- turn off fcntl on windows

digits/config/caffe_option.py

@@ -65,6 +65,8 @@ def validate(cls, value):
  if value == '<PATHS>':
  # Find the executable
  executable = cls.find_executable('caffe')
+ if not executable:
+ executable = cls.find_executable('caffe.exe')
  if not executable:
  raise config_option.BadValue('caffe binary not found in PATH')
  cls.validate_version(executable)
@@ -187,6 +189,9 @@ def get_version(executable):
  elif platform.system() == 'Darwin':
  # XXX: guess and let the user figure out errors later
  return (0,11,0)
+ elif platform.system() == 'Windows':
+ # XXX: guess and let the user figure out errors later
+ return (0,12,0)
  else:
  print 'WARNING: platform "%s" not supported' % platform.system()
  return None
@@ -197,6 +202,8 @@ def _set_config_dict_value(self, value):
  else:
  if value == '<PATHS>':
  executable = self.find_executable('caffe')
+ if not executable:
+ executable = self.find_executable('caffe.exe')
  else:
  executable = os.path.join(value, 'build', 'tools', 'caffe')
 

digits/model/tasks/caffe_train.py

@@ -231,7 +231,7 @@ def save_prototxt_files(self):
  val_data_layer.data_param.backend = caffe_pb2.DataParameter.LMDB
  if self.use_mean:
  mean_pixel = None
- with open(self.dataset.path(self.dataset.train_db_task().mean_file)) as f:
+ with open(self.dataset.path(self.dataset.train_db_task().mean_file),'rb') as f:
  blob = caffe_pb2.BlobProto()
  blob.MergeFromString(f.read())
  mean = np.reshape(blob.data,

digits/task.py

@@ -15,6 +15,8 @@
 from config import config_value
 from status import Status, StatusCls
 
+import platform
+
 # NOTE: Increment this everytime the pickled version changes
 PICKLE_VERSION = 1
 
@@ -128,7 +130,7 @@ def path(self, filename, relative=False):
  path = os.path.join(self.job_dir, filename)
  if relative:
  path = os.path.relpath(path, config_value('jobs_dir'))
- return str(path)
+ return str(path).replace("\\","/")
 
  def ready_to_queue(self):
  """
@@ -193,7 +195,7 @@ def run(self, resources):
  stdout=subprocess.PIPE,
  stderr=subprocess.STDOUT,
  cwd=self.job_dir,
- close_fds=True,
+ close_fds=False if platform.system() == 'Windows' else True,
  )
 
  try:

digits/utils/__init__.py

@@ -2,12 +2,15 @@
 
 import os
 import math
-import fcntl
 import locale
 from random import uniform
 from urlparse import urlparse
 from io import BlockingIOError
 import inspect
+import platform
+
+if not platform.system() == 'Windows':
+ import fcntl
 
 HTTP_TIMEOUT = 6.05
 
@@ -27,8 +30,9 @@ def nonblocking_readlines(f):
  Newlines are normalized to the Unix standard.
  """
  fd = f.fileno()
- fl = fcntl.fcntl(fd, fcntl.F_GETFL)
- fcntl.fcntl(fd, fcntl.F_SETFL, fl | os.O_NONBLOCK)
+ if not platform.system() == 'Windows':
+ fl = fcntl.fcntl(fd, fcntl.F_GETFL)
+ fcntl.fcntl(fd, fcntl.F_SETFL, fl | os.O_NONBLOCK)
  enc = locale.getpreferredencoding(False)
 
  buf = bytearray()

docs/API.md

@@ -1,6 +1,6 @@
 # REST API
 
-*Generated Aug 05, 2015*
+*Generated Aug 07, 2015*
 
 DIGITS exposes its internal functionality through a REST API. You can access these endpoints by performing a GET or POST on the route, and a JSON object will be returned.
 

docs/FlaskRoutes.md

@@ -1,6 +1,6 @@
 # Flask Routes
 
-*Generated Aug 05, 2015*
+*Generated Aug 07, 2015*
 
 Documentation on the various routes used internally for the web application.
 
@@ -334,7 +334,7 @@ Location: [`digits/model/views.py@90`](../digits/model/views.py#L90)
 
 Methods: **GET**
 
-Location: [`digits/views.py@245`](../digits/views.py#L245)
+Location: [`digits/views.py@242`](../digits/views.py#L242)
 
 ### `/files/<path:path>`
 

scripts/generate_docs.py

@@ -158,10 +158,10 @@ def _print_route(self, route):
  )
  filename = os.path.normpath(route['location']['filename'])
  if filename.startswith(digits_root):
- filename = os.path.relpath(filename, digits_root)
+ filename = os.path.relpath(filename, digits_root).replace("\\","/")
  self.w('Location: [`%s@%s`](%s#L%s)' % (
  filename, route['location']['line'],
- os.path.join('..', filename), route['location']['line'],
+ os.path.join('..', filename).replace("\\","/"), route['location']['line'],
  ))
  self.w()
 

tools/create_db.py

@@ -23,7 +23,7 @@
 
 import numpy as np
 import PIL.Image
-import leveldb
+
 import lmdb
 from cStringIO import StringIO
 # must call digits.config.load_config() before caffe to set the path
@@ -36,6 +36,12 @@
 
 logger = logging.getLogger('digits.tools.create_db')
 
+try:
+ import leveldb
+except ImportError:
+ logger.warning('leveldb support is missing')
+
+
 class DbCreator:
  """
  Creates a database for a neural network imageset
@@ -286,7 +292,7 @@ def create(self, input_file, width, height,
  blob.channels, blob.height, blob.width = data.shape
  blob.data.extend(data.astype(float).flat)
 
- with open(mean_file, 'w') as outfile:
+ with open(mean_file, 'wb') as outfile:
  outfile.write(blob.SerializeToString())
  elif mean_file.lower().endswith(('.jpg', '.jpeg', '.png')):
  image = PIL.Image.fromarray(mean)