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Changed gaze tracking to always use single thread to avoid excessive CPU usage.

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This commit is contained in:
Emiliana 2021-09-11 15:57:03 +02:00
parent 44d97a967c
commit 1264cc255c
1 changed files with 5 additions and 10 deletions
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13
tracker.py
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@ -140,7 +140,7 @@ def worker_thread(session, frame, input, crop_info, queue, input_name, idx, trac
conf, lms = tracker.landmarks(output[0], crop_info)
if conf > tracker.threshold:
try:
eye_state = tracker.get_eye_state(frame, lms, single=True)
eye_state = tracker.get_eye_state(frame, lms)
except:
eye_state = [(1.0, 0.0, 0.0, 0.0), (1.0, 0.0, 0.0, 0.0)]
queue.put((session, conf, (lms, eye_state), crop_info, idx))
@ -548,14 +548,12 @@ class Tracker():
self.input_name = self.session.get_inputs()[0].name
options = onnxruntime.SessionOptions()
options.inter_op_num_threads = 1
options.intra_op_num_threads = max(max_threads,4)
#options.intra_op_num_threads = max(max_threads,4)
options.intra_op_num_threads = 1
options.execution_mode = onnxruntime.ExecutionMode.ORT_SEQUENTIAL
options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
options.log_severity_level = 3
self.gaze_model = onnxruntime.InferenceSession(os.path.join(model_base_path, "mnv3_gaze32_split_opt.onnx"), sess_options=options)
options.intra_op_num_threads = 1
self.gaze_model_single = onnxruntime.InferenceSession(os.path.join(model_base_path, "mnv3_gaze32_split_opt.onnx"), sess_options=options)
self.detection = onnxruntime.InferenceSession(os.path.join(model_base_path, "mnv3_detection_opt.onnx"), sess_options=options)
self.faces = []
@ -922,7 +920,7 @@ class Tracker():
frame = frame[y1:y2, x1:x2]
return frame, lms, offset
def get_eye_state(self, frame, lms, single=False):
def get_eye_state(self, frame, lms):
if self.no_gaze:
return [(1.0, 0.0, 0.0, 0.0), (1.0, 0.0, 0.0, 0.0)]
lms = np.array(lms)
@ -938,9 +936,6 @@ class Tracker():
return [(1.0, 0.0, 0.0, 0.0), (1.0, 0.0, 0.0, 0.0)]
both_eyes = np.concatenate((right_eye, left_eye))
results = None
if single:
results = self.gaze_model_single.run([], {self.input_name: both_eyes})
else:
results = self.gaze_model.run([], {self.input_name: both_eyes})
open = [0, 0]
open[0] = 1#results[1][0].argmax()