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-rw-r--r--src/argaze/ArFeatures.py24
-rw-r--r--src/argaze/ArUcoMarkers/ArUcoDetector.py4
2 files changed, 14 insertions, 14 deletions
diff --git a/src/argaze/ArFeatures.py b/src/argaze/ArFeatures.py
index 6c9eab1..b4b1e39 100644
--- a/src/argaze/ArFeatures.py
+++ b/src/argaze/ArFeatures.py
@@ -495,13 +495,13 @@ class ArFrame():
if self.gaze_movement_identifier:
# Store movement identification start date
- identification_start = time.time()
+ identification_start = time.perf_counter()
# Identify finished gaze movement
temp_gaze_movement = self.gaze_movement_identifier.identify(timestamp, self.__gaze_position)
# Assess movement identification time in ms
- times['gaze_movement_identifier'] = (time.time() - identification_start) * 1e3
+ times['gaze_movement_identifier'] = (time.perf_counter() - identification_start) * 1e3
# Use given identified gaze movement
else:
@@ -514,13 +514,13 @@ class ArFrame():
if GazeFeatures.is_fixation(temp_gaze_movement):
# Store aoi matching start date
- matching_start = time.time()
+ matching_start = time.perf_counter()
# Does the finished fixation match an aoi?
self.__update_looked_aoi_data(temp_gaze_movement)
# Assess aoi matching time in ms
- times['aoi_matcher'] = (time.time() - matching_start) * 1e3
+ times['aoi_matcher'] = (time.perf_counter() - matching_start) * 1e3
# Append fixation to scan path
if self.scan_path != None:
@@ -538,13 +538,13 @@ class ArFrame():
for aoi_scan_path_analyzer_type, aoi_scan_path_analyzer in self.aoi_scan_path_analyzers.items():
# Store aoi scan step analysis start date
- aoi_scan_step_analysis_start = time.time()
+ aoi_scan_step_analysis_start = time.perf_counter()
# Analyze aoi scan path
aoi_scan_path_analyzer.analyze(self.aoi_scan_path)
# Assess aoi scan step analysis time in ms
- times['aoi_scan_step_analyzers'][aoi_scan_path_analyzer_type] = (time.time() - aoi_scan_step_analysis_start) * 1e3
+ times['aoi_scan_step_analyzers'][aoi_scan_path_analyzer_type] = (time.perf_counter() - aoi_scan_step_analysis_start) * 1e3
# Store analysis
aoi_scan_step_analysis[aoi_scan_path_analyzer_type] = aoi_scan_path_analyzer.analysis
@@ -565,13 +565,13 @@ class ArFrame():
for scan_path_analyzer_type, scan_path_analyzer in self.scan_path_analyzers.items():
# Store scan step analysis start date
- scan_step_analysis_start = time.time()
+ scan_step_analysis_start = time.perf_counter()
# Analyze aoi scan path
scan_path_analyzer.analyze(self.scan_path)
# Assess scan step analysis time in ms
- times['scan_step_analyzers'][scan_path_analyzer_type] = (time.time() - scan_step_analysis_start) * 1e3
+ times['scan_step_analyzers'][scan_path_analyzer_type] = (time.perf_counter() - scan_step_analysis_start) * 1e3
# Store analysis
scan_step_analysis[scan_path_analyzer_type] = scan_path_analyzer.analysis
@@ -591,19 +591,19 @@ class ArFrame():
temp_gaze_movement = current_fixation
# Store aoi matching start date
- matching_start = time.time()
+ matching_start = time.perf_counter()
# Does the current fixation match an aoi?
self.__update_looked_aoi_data(current_fixation)
# Assess aoi matching time in ms
- times['aoi_matcher'] = (time.time() - matching_start) * 1e3
+ times['aoi_matcher'] = (time.perf_counter() - matching_start) * 1e3
# Update heatmap
if self.heatmap:
# Store heatmap start date
- heatmap_start = time.time()
+ heatmap_start = time.perf_counter()
# Scale gaze position value
scale = numpy.array([self.heatmap.size[0] / self.size[0], self.heatmap.size[1] / self.size[1]])
@@ -612,7 +612,7 @@ class ArFrame():
self.heatmap.update(self.__gaze_position.value * scale)
# Assess heatmap time in ms
- times['heatmap'] = (time.time() - heatmap_start) * 1e3
+ times['heatmap'] = (time.perf_counter() - heatmap_start) * 1e3
except Exception as e:
diff --git a/src/argaze/ArUcoMarkers/ArUcoDetector.py b/src/argaze/ArUcoMarkers/ArUcoDetector.py
index c750e1b..5076f3d 100644
--- a/src/argaze/ArUcoMarkers/ArUcoDetector.py
+++ b/src/argaze/ArUcoMarkers/ArUcoDetector.py
@@ -190,13 +190,13 @@ class ArUcoDetector():
self.__detected_markers, self.__detected_markers_corners, self.__detected_markers_ids = {}, [], []
# Store marker detection start date
- detection_start = time.time()
+ detection_start = time.perf_counter()
# Detect markers into gray picture
self.__detected_markers_corners, self.__detected_markers_ids, _ = aruco.detectMarkers(cv.cvtColor(image, cv.COLOR_BGR2GRAY), self.dictionary.markers, parameters = self.parameters.internal)
# Assess marker detection time in ms
- detection_time = (time.time() - detection_start) * 1e3
+ detection_time = (time.perf_counter() - detection_start) * 1e3
# Is there detected markers ?
if len(self.__detected_markers_corners) > 0: