forked from Github/frigate
removing motion detection
This commit is contained in:
blakeblackshear
@@ -47,7 +47,7 @@ def detect_objects(prepped_frame_array, prepped_frame_time,
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objects = engine.DetectWithInputTensor(prepped_frame_copy, threshold=0.5, top_k=3)
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# time.sleep(0.1)
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# objects = []
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print(engine.get_inference_time())
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# print(engine.get_inference_time())
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# put detected objects in the queue
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if objects:
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for obj in objects:
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@@ -109,7 +109,7 @@ class PreppedQueueProcessor(threading.Thread):
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# should this be a region class?
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class FramePrepper(threading.Thread):
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def __init__(self, shared_frame, frame_time, frame_ready,
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frame_lock, motion_detected,
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frame_lock,
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region_size, region_x_offset, region_y_offset,
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prepped_frame_queue):
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@@ -118,7 +118,6 @@ class FramePrepper(threading.Thread):
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self.frame_time = frame_time
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self.frame_ready = frame_ready
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self.frame_lock = frame_lock
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self.motion_detected = motion_detected
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self.region_size = region_size
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self.region_x_offset = region_x_offset
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self.region_y_offset = region_y_offset
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@@ -129,9 +128,6 @@ class FramePrepper(threading.Thread):
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while True:
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now = datetime.datetime.now().timestamp()
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# wait until motion is detected
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self.motion_detected.wait()
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with self.frame_ready:
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# if there isnt a frame ready for processing or it is old, wait for a new frame
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if self.frame_time.value == frame_time or (now - self.frame_time.value) > 0.5:
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@@ -30,114 +30,92 @@ class ObjectParser(threading.Thread):
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self._objects_parsed.notify_all()
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class ObjectCleaner(threading.Thread):
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def __init__(self, objects_parsed, detected_objects, motion_changed, motion_regions):
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def __init__(self, objects_parsed, detected_objects):
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threading.Thread.__init__(self)
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self._objects_parsed = objects_parsed
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self._detected_objects = detected_objects
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self.motion_changed = motion_changed
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self.motion_regions = motion_regions
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def run(self):
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while True:
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# while there is motion
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while len([r for r in self.motion_regions if r.is_set()]) > 0:
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# wait a bit before checking for expired frames
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time.sleep(0.2)
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# wait a bit before checking for expired frames
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time.sleep(0.2)
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# expire the objects that are more than 1 second old
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now = datetime.datetime.now().timestamp()
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# look for the first object found within the last second
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# (newest objects are appended to the end)
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detected_objects = self._detected_objects.copy()
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# expire the objects that are more than 1 second old
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now = datetime.datetime.now().timestamp()
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# look for the first object found within the last second
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# (newest objects are appended to the end)
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detected_objects = self._detected_objects.copy()
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#print([round(now-obj['frame_time'],2) for obj in detected_objects])
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num_to_delete = 0
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for obj in detected_objects:
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if now-obj['frame_time']<2:
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break
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num_to_delete += 1
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if num_to_delete > 0:
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del self._detected_objects[:num_to_delete]
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#print([round(now-obj['frame_time'],2) for obj in detected_objects])
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num_to_delete = 0
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for obj in detected_objects:
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if now-obj['frame_time']<2:
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break
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num_to_delete += 1
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if num_to_delete > 0:
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del self._detected_objects[:num_to_delete]
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# notify that parsed objects were changed
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with self._objects_parsed:
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self._objects_parsed.notify_all()
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# notify that parsed objects were changed
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with self._objects_parsed:
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self._objects_parsed.notify_all()
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# wait for the global motion flag to change
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with self.motion_changed:
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self.motion_changed.wait()
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# Maintains the frame and person with the highest score from the most recent
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# motion event
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class BestPersonFrame(threading.Thread):
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def __init__(self, objects_parsed, recent_frames, detected_objects, motion_changed, motion_regions):
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def __init__(self, objects_parsed, recent_frames, detected_objects):
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threading.Thread.__init__(self)
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self.objects_parsed = objects_parsed
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self.recent_frames = recent_frames
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self.detected_objects = detected_objects
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self.motion_changed = motion_changed
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self.motion_regions = motion_regions
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self.best_person = None
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self.best_frame = None
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def run(self):
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motion_start = 0.0
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motion_end = 0.0
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while True:
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# while there is motion
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while len([r for r in self.motion_regions if r.is_set()]) > 0:
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# wait until objects have been parsed
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with self.objects_parsed:
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self.objects_parsed.wait()
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# wait until objects have been parsed
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with self.objects_parsed:
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self.objects_parsed.wait()
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# make a copy of detected objects
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detected_objects = self.detected_objects.copy()
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detected_people = [obj for obj in detected_objects if obj['name'] == 'person']
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# make a copy of the recent frames
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recent_frames = self.recent_frames.copy()
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# make a copy of detected objects
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detected_objects = self.detected_objects.copy()
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detected_people = [obj for obj in detected_objects if obj['name'] == 'person']
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# make a copy of the recent frames
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recent_frames = self.recent_frames.copy()
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# get the highest scoring person
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new_best_person = max(detected_people, key=lambda x:x['score'], default=self.best_person)
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# get the highest scoring person
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new_best_person = max(detected_people, key=lambda x:x['score'], default=self.best_person)
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# if there isnt a person, continue
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if new_best_person is None:
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continue
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# if there isnt a person, continue
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if new_best_person is None:
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continue
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# if there is no current best_person
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if self.best_person is None:
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# if there is no current best_person
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if self.best_person is None:
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self.best_person = new_best_person
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# if there is already a best_person
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else:
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now = datetime.datetime.now().timestamp()
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# if the new best person is a higher score than the current best person
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# or the current person is more than 1 minute old, use the new best person
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if new_best_person['score'] > self.best_person['score'] or (now - self.best_person['frame_time']) > 60:
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self.best_person = new_best_person
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# if there is already a best_person
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else:
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now = datetime.datetime.now().timestamp()
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# if the new best person is a higher score than the current best person
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# or the current person is more than 1 minute old, use the new best person
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if new_best_person['score'] > self.best_person['score'] or (now - self.best_person['frame_time']) > 60:
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self.best_person = new_best_person
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if not self.best_person is None and self.best_person['frame_time'] in recent_frames:
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best_frame = recent_frames[self.best_person['frame_time']]
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best_frame = cv2.cvtColor(best_frame, cv2.COLOR_BGR2RGB)
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# draw the bounding box on the frame
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vis_util.draw_bounding_box_on_image_array(best_frame,
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self.best_person['ymin'],
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self.best_person['xmin'],
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self.best_person['ymax'],
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self.best_person['xmax'],
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color='red',
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thickness=2,
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display_str_list=["{}: {}%".format(self.best_person['name'],int(self.best_person['score']*100))],
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use_normalized_coordinates=False)
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if not self.best_person is None and self.best_person['frame_time'] in recent_frames:
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best_frame = recent_frames[self.best_person['frame_time']]
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best_frame = cv2.cvtColor(best_frame, cv2.COLOR_BGR2RGB)
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# draw the bounding box on the frame
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vis_util.draw_bounding_box_on_image_array(best_frame,
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self.best_person['ymin'],
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self.best_person['xmin'],
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self.best_person['ymax'],
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self.best_person['xmax'],
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color='red',
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thickness=2,
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display_str_list=["{}: {}%".format(self.best_person['name'],int(self.best_person['score']*100))],
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use_normalized_coordinates=False)
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# convert back to BGR
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self.best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)
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motion_end = datetime.datetime.now().timestamp()
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# wait for the global motion flag to change
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with self.motion_changed:
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self.motion_changed.wait()
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motion_start = datetime.datetime.now().timestamp()
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# convert back to BGR
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self.best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)
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@@ -54,42 +54,34 @@ def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_s
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# Stores 2 seconds worth of frames when motion is detected so they can be used for other threads
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class FrameTracker(threading.Thread):
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def __init__(self, shared_frame, frame_time, frame_ready, frame_lock, recent_frames, motion_changed, motion_regions):
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def __init__(self, shared_frame, frame_time, frame_ready, frame_lock, recent_frames):
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threading.Thread.__init__(self)
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self.shared_frame = shared_frame
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self.frame_time = frame_time
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self.frame_ready = frame_ready
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self.frame_lock = frame_lock
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self.recent_frames = recent_frames
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self.motion_changed = motion_changed
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self.motion_regions = motion_regions
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def run(self):
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frame_time = 0.0
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while True:
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# while there is motion
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while len([r for r in self.motion_regions if r.is_set()]) > 0:
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now = datetime.datetime.now().timestamp()
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# wait for a frame
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with self.frame_ready:
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# if there isnt a frame ready for processing or it is old, wait for a signal
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if self.frame_time.value == frame_time or (now - self.frame_time.value) > 0.5:
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self.frame_ready.wait()
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# lock and make a copy of the frame
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with self.frame_lock:
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frame = self.shared_frame.copy()
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frame_time = self.frame_time.value
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# add the frame to recent frames
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self.recent_frames[frame_time] = frame
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now = datetime.datetime.now().timestamp()
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# wait for a frame
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with self.frame_ready:
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# if there isnt a frame ready for processing or it is old, wait for a signal
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if self.frame_time.value == frame_time or (now - self.frame_time.value) > 0.5:
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self.frame_ready.wait()
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# lock and make a copy of the frame
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with self.frame_lock:
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frame = self.shared_frame.copy()
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frame_time = self.frame_time.value
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# add the frame to recent frames
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self.recent_frames[frame_time] = frame
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# delete any old frames
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stored_frame_times = list(self.recent_frames.keys())
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for k in stored_frame_times:
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if (now - k) > 2:
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del self.recent_frames[k]
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# wait for the global motion flag to change
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with self.motion_changed:
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self.motion_changed.wait()
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# delete any old frames
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stored_frame_times = list(self.recent_frames.keys())
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for k in stored_frame_times:
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if (now - k) > 2:
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del self.recent_frames[k]
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