def run_benchmarks(benchmark_params, test_root, force=False):
"""Run the benchmarks
For every row in benchmark params, run a trace on the input video
using the params specified.
benchmark_params: DataFrame with columns corresponding to keywords
to pass to pipeline_trace. Should have columns 'name',
'input_video', 'chunk_sz_frames', 'epoch_sz_frames',
'frame_start', 'frame_stop', 'n_trace_processes', etc
Returns:
test_results, durations
test_results : Dict from test['name'] to results read from hdf5 file
durations : list of durations taken
"""
WhiskiWrap.utils.probe_needed_commands()
test_results = {}
durations = []
for idx, test in benchmark_params.iterrows():
print(test['name'])
test_dir = os.path.expanduser(os.path.join(test_root, test['name']))
fn = setup_session_directory(test_dir,
test['input_video'],
force=force)
# Run
start_time = time.time()
WhiskiWrap.pipeline_trace(fn.video('mp4'),
fn.hdf5,
chunk_sz_frames=test['chunk_sz_frames'],
epoch_sz_frames=test['epoch_sz_frames'],
frame_start=test['frame_start'],
frame_stop=test['frame_stop'],
n_trace_processes=test['n_trace_processes'])
stop_time = time.time()
durations.append(stop_time - start_time)
# Get the summary
with tables.open_file(fn.hdf5) as fi:
test_results[test['name']] = pandas.DataFrame.from_records(
fi.root.summary.read())
return test_results, durations
def run_benchmarks(benchmark_params, test_root, force=False):
"""Run the benchmarks
For every row in benchmark params, run a trace on the input video
using the params specified.
benchmark_params: DataFrame with columns corresponding to keywords
to pass to pipeline_trace. Should have columns 'name',
'input_video', 'chunk_sz_frames', 'epoch_sz_frames',
'frame_start', 'frame_stop', 'n_trace_processes', etc
Returns:
test_results, durations
test_results : Dict from test['name'] to results read from hdf5 file
durations : list of durations taken
"""
WhiskiWrap.utils.probe_needed_commands()
test_results = {}
durations = []
for idx, test in benchmark_params.iterrows():
print test['name']
test_dir = os.path.expanduser(os.path.join(test_root, test['name']))
fn = setup_session_directory(test_dir, test['input_video'], force=force)
# Run
start_time = time.time()
WhiskiWrap.pipeline_trace(
fn.video('mp4'),
fn.hdf5,
chunk_sz_frames=test['chunk_sz_frames'],
epoch_sz_frames=test['epoch_sz_frames'],
frame_start=test['frame_start'],
frame_stop=test['frame_stop'],
n_trace_processes=test['n_trace_processes'])
stop_time = time.time()
durations.append(stop_time - start_time)
# Get the summary
with tables.open_file(fn.hdf5) as fi:
test_results[test['name']] = pandas.DataFrame.from_records(
fi.root.summary.read())
return test_results, durations
assert args.video_path is not None, 'Video path must be specified when video path is given.'
video_path = args.video_path
# working directory is always the script directory
wdir = os.getcwd()
# get video name
video_fname = os.path.basename(video_path)
video_name = ''.join(video_fname.split('.')[:-1])
# output_path has the same name of the video name plus whiki_
output_path = os.path.join(wdir, 'whiski_' + video_name)
# creates output path if it doesn't exists
if not os.path.exists(output_path):
warn('out path didn\'t exist creating output path ' + output_path)
os.mkdir(output_path)
# copies video if it is not there (in the output path)
input_video = os.path.join(output_path, video_fname)
if not os.path.exists(input_video):
warn('input video didn\'t exist coping from source ' + output_path)
shutil.copy(video_path, input_video)
output_file = os.path.join(output_path, video_name + '.hdf5')
freeze_support()
input_video = os.path.expanduser(input_video)
output_file = os.path.expanduser(output_file)
print('input_video ', input_video)
print('output_file', output_file)
WhiskiWrap.pipeline_trace(input_video,
output_file,
n_trace_processes=4,
chunk_sz_frames=100)
