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WIP: convert to camera class

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blakeblackshear
2019-03-29 20:49:27 -05:00
parent 8774e537dc
commit 0279121d77
4 changed files with 223 additions and 206 deletions
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46
frigate/objects.py
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@@ -4,53 +4,17 @@ import threading
import cv2
from object_detection.utils import visualization_utils as vis_util
class ObjectParser(threading.Thread):
def __init__(self, object_queue, objects_parsed, detected_objects, regions):
def __init__(self, cameras, object_queue, detected_objects, regions):
threading.Thread.__init__(self)
self._object_queue = object_queue
self._objects_parsed = objects_parsed
self._detected_objects = detected_objects
self.cameras = cameras
self.object_queue = object_queue
self.regions = regions
def run(self):
# frame_times = {}
while True:
obj = self._object_queue.get()
# filter out persons
# [obj['score'] for obj in detected_objects if obj['name'] == 'person']
if obj['name'] == 'person':
person_area = (obj['xmax']-obj['xmin'])*(obj['ymax']-obj['ymin'])
# find the matching region
region = None
for r in self.regions:
if (
obj['xmin'] >= r['x_offset'] and
obj['ymin'] >= r['y_offset'] and
obj['xmax'] <= r['x_offset']+r['size'] and
obj['ymax'] <= r['y_offset']+r['size']
):
region = r
break
# if the min person area is larger than the
# detected person, don't add it to detected objects
if region and region['min_person_area'] > person_area:
continue
# frame_time = obj['frame_time']
# if frame_time in frame_times:
# if frame_times[frame_time] == 7:
# del frame_times[frame_time]
# else:
# frame_times[frame_time] += 1
# else:
# frame_times[frame_time] = 1
# print(frame_times)
self._detected_objects.append(obj)
# notify that objects were parsed
with self._objects_parsed:
self._objects_parsed.notify_all()
obj = self.object_queue.get()
self.cameras[obj['camera_name']].add_object(obj)
class ObjectCleaner(threading.Thread):
def __init__(self, objects_parsed, detected_objects):