def cheetah_render(content, params):
return CTemplate(content, searchList=[params]).respond()
def _generate_attributes(self, video_file, video_work_dir):
"""
Run actual sun_attributes code on video, outputting a file that is the
concatenation of frame feature products (checkpoint file) and returning
the resultant matrix. The output file will be a numpy binary file
storing a 2D array object.
If the output file already exists, we will assume that the work as
already been completed and will load and return that file's matrix.
:raises RuntimeError: Couldn't create raw scores due to error in
runtime. This can either be due to frame extraction failure or
failure at running the SUN attributes executable.
:param video_file: Video for processing
:type video_file: str
:param video_work_dir: Directory to store work in
:type video_work_dir: str
:return: 2D numpy array object that is the combined frame feature
vectors, or attribute scores. If None is returned, that means scores
couldn't be produced on this video.
:rtype: numpy.ndarray
"""
# video frame extraction
#
# extracting jpb because the MATLAB code only works with jpg files
# apparently...
#
# exiting failure if no frames extracted.
#
frame2img, _ = self.mp4_extract_video_frames(video_file, 'jpg')
# run output vars
f_result_output_dir = osp.join(video_work_dir, 'frame_results')
self.create_dir(f_result_output_dir)
output_files = {}
tmp_output_files = {} # tmp version of output_files map
of_not_present = [] # frames for which no non-temp output present
# Predict output files we will need for images specified/produced
# If one or more of the predicted output files doesn't exist in
# their predicted location, queue it to be processed.
for frame, img_file in sorted(frame2img.items()):
output_files[frame] = osp.join(f_result_output_dir,
'frm%06d.features' % frame)
tmp_output_files[frame] = \
self.tempify_filename(output_files[frame])
if not osp.isfile(output_files[frame]):
of_not_present.append(frame)
# Only create a work file and process if anything actually needs to
# be processed
if of_not_present:
# remove old temp files if present (i don't know what the MATLAB
# code might do with a partially written file, i.e. if it will
# append to it or not)
self._log.debug("removing pre-existing temp frame work files")
for f in tmp_output_files.values():
if osp.isfile(f):
os.remove(f)
# Create actual work file, overwriting any that might already be
# present.
work_file = osp.join(video_work_dir, 'sa_work_file.txt')
with open(work_file, 'w') as wfile:
for frame in of_not_present:
wfile.write("%s,%s\n" % (frame2img[frame],
tmp_output_files[frame]))
# Generating configuration file from template, overwriting an
# existing one if present (things may be different).
config_file = osp.join(video_work_dir, 'sa_config.xml')
sa_tmp_folder = \
self.create_dir(osp.join(video_work_dir, 'sa_tmp'))
sl = {'sa_src_dir': self._sa_src_dir,
'working_dir': sa_tmp_folder}
with open(config_file, 'w') as cfile:
cfile.write(str(CTemplate(file=self._config_tmpl,
searchList=sl)))
run_args = [self._sa_runner, self._mcr_root, work_file,
config_file]
self._log.debug("call: %s", ' '.join(run_args))
log_file = osp.join(video_work_dir, 'last_run.log')
with open(log_file, 'w') as lf:
# MATLAB is known to rarely timeout indefinitely. Using ex
start = time.time()
p = subprocess.Popen(run_args, stdout=lf, stderr=lf)
while p.poll() is None:
# check if timeout exceeded, kicking the bucket if so
if (time.time() - start) > self._matlab_run_timeout_seconds:
p.terminate()
raise RuntimeError(
"MATLAB processing exceeded configured timeout "
"(%.1f minutes). Check run log file for possible "
"details as to why: %s",
self._matlab_run_timeout_seconds / 60.0, log_file
)
time.sleep(self._timeout_poll_interval)
if p.returncode != 0:
raise RuntimeError("Failed to process sun_attributes "
"for video %s with return code %s. "
"Check log file: %s"
% (video_file, str(p.returncode), log_file))
# Run successful, check that configured tmp files exist and
# rename them to the official output names.
for frame in of_not_present:
if not osp.isfile(tmp_output_files[frame]):
raise RuntimeError("sun_attributes failed to produce "
"output for requested frame %d. "
"Check that it is actually present "
"in the generated work file (%s) "
"as well as check the log file (%s)."
% (frame, work_file, log_file))
os.rename(tmp_output_files[frame], output_files[frame])
# Remove temp work files generated by sun_attributes
self._log.debug("removing sa temp working directory")
shutil.rmtree(sa_tmp_folder)
###
# Combination
#
# First, need to construct the combined matrix, which is just each
# frame's results stacked from top to bottom in frame order.
#
self._log.debug("creating raw combined features matrix")
combined_matrix = []
for frm, features_file in sorted(output_files.items()):
self._log.debug("-> adding frame %d : %s", frm, features_file)
combined_matrix.append(np.loadtxt(features_file))
combined_matrix = np.array(combined_matrix) # make 2D array of list
return combined_matrix
