def processing_statistics(
data: DataSet,
reconstructions: List[types.Reconstruction]) -> Dict[str, Any]:
steps = {
"Feature Extraction": "features.json",
"Features Matching": "matches.json",
"Tracks Merging": "tracks.json",
"Reconstruction": "reconstruction.json",
}
steps_times = {}
for step_name, report_file in steps.items():
file_path = os.path.join(data.data_path, "reports", report_file)
if os.path.exists(file_path):
with io.open_rt(file_path) as fin:
obj = io.json_load(fin)
else:
obj = {}
if "wall_time" in obj:
steps_times[step_name] = obj["wall_time"]
elif "wall_times" in obj:
steps_times[step_name] = sum(obj["wall_times"].values())
else:
steps_times[step_name] = -1
stats = {}
stats["steps_times"] = steps_times
stats["steps_times"]["Total Time"] = sum(
filter(lambda x: x >= 0, steps_times.values()))
try:
stats["date"] = datetime.datetime.fromtimestamp(
data.io_handler.timestamp(data._reconstruction_file(
None))).strftime("%d/%m/%Y at %H:%M:%S")
except FileNotFoundError:
stats["date"] = "unknown"
start_ct, end_ct = start_end_capture_time(reconstructions)
if start_ct is not None and end_ct is not None:
stats["start_date"] = datetime.datetime.fromtimestamp(
start_ct).strftime("%d/%m/%Y at %H:%M:%S")
stats["end_date"] = datetime.datetime.fromtimestamp(end_ct).strftime(
"%d/%m/%Y at %H:%M:%S")
else:
stats["start_date"] = "unknown"
stats["end_date"] = "unknown"
default_max = 1e30
min_x, min_y, max_x, max_y = default_max, default_max, 0, 0
for rec in reconstructions:
for shot in rec.shots.values():
o = shot.pose.get_origin()
min_x = min(min_x, o[0])
min_y = min(min_y, o[1])
max_x = max(max_x, o[0])
max_y = max(max_y, o[1])
stats["area"] = (max_x - min_x) * (max_y -
min_y) if min_x != default_max else -1
return stats
def processing_statistics(data: DataSet, reconstructions):
steps = {
"Feature Extraction": "features.json",
"Features Matching": "matches.json",
"Tracks Merging": "tracks.json",
"Reconstruction": "reconstruction.json",
}
steps_times = {}
for step_name, report_file in steps.items():
file_path = os.path.join(data.data_path, "reports", report_file)
if os.path.exists(file_path):
with io.open_rt(file_path) as fin:
obj = io.json_load(fin)
else:
obj = {}
if "wall_time" in obj:
steps_times[step_name] = obj["wall_time"]
elif "wall_times" in obj:
steps_times[step_name] = sum(obj["wall_times"].values())
else:
steps_times[step_name] = -1
stats = {}
stats["steps_times"] = steps_times
stats["steps_times"]["Total Time"] = sum(
filter(lambda x: x >= 0, steps_times.values()))
stats["date"] = datetime.datetime.fromtimestamp(
os.path.getmtime(
data._reconstruction_file(None))).strftime("%d/%m/%Y at %H:%M:%S")
min_x, min_y, max_x, max_y = 1e30, 1e30, 0, 0
for rec in reconstructions:
for shot in rec.shots.values():
o = shot.pose.get_origin()
min_x = min(min_x, o[0])
min_y = min(min_y, o[1])
max_x = max(max_x, o[0])
max_y = max(max_y, o[1])
stats["area"] = (max_x - min_x) * (max_y - min_y)
return stats
