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https://github.com/blakeblackshear/frigate.git
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add layout calculations
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@ -1,12 +1,14 @@
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import datetime
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import math
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import multiprocessing as mp
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import queue
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import signal
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import subprocess as sp
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import threading
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import numpy as np
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from multiprocessing import shared_memory
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from wsgiref.simple_server import make_server
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import numpy as np
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from setproctitle import setproctitle
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from ws4py.server.wsgirefserver import (
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WebSocketWSGIHandler,
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@ -68,29 +70,80 @@ class BroadcastThread(threading.Thread):
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class BirdsEyeFrameManager:
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def __init__(self, height, width):
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frame_shape = (height, width)
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yuv_shape = (height * 3 // 2, width)
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self.frame = np.ndarray(yuv_shape, dtype=np.uint8)
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self.frame_shape = (height, width)
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self.yuv_shape = (height * 3 // 2, width)
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self.frame = np.ndarray(self.yuv_shape, dtype=np.uint8)
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# initialize the frame as black and with the frigate logo
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self.blank_frame = np.zeros(yuv_shape, np.uint8)
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self.blank_frame = np.zeros(self.yuv_shape, np.uint8)
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self.blank_frame[:] = 128
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self.blank_frame[0 : frame_shape[0], 0 : frame_shape[1]] = 16
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self.blank_frame[0 : self.frame_shape[0], 0 : self.frame_shape[1]] = 16
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self.frame[:] = self.blank_frame
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def update(self, camera, object_count, motion_count, frame_time, frame):
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# determine how many cameras are tracking objects (or recently were)
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self.last_active_frames = {}
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self.camera_layout = []
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def clear_frame(self):
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self.frame[:] = self.blank_frame
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def update(self, camera, object_count, motion_count, frame_time, frame) -> bool:
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# maintain time of most recent active frame for each camera
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if object_count > 0:
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self.last_active_frames[camera] = frame_time
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# TODO: avoid the remaining work if exceeding 5 fps and return False
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# determine how many cameras are tracking objects within the last 30 seconds
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now = datetime.datetime.now().timestamp()
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active_cameras = [
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cam
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for cam, frame_time in self.last_active_frames.items()
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if now - frame_time < 30
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]
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if len(active_cameras) == 0 and len(self.camera_layout) == 0:
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return False
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# if the sqrt of the layout and the active cameras don't round to the same value,
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# we need to resize the layout
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if round(math.sqrt(len(active_cameras))) != round(
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math.sqrt(len(self.camera_layout))
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):
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# decide on a layout for the birdseye view (try to avoid too much churn)
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# calculate position of each camera
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self.columns = math.ceil(math.sqrt(len(active_cameras)))
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self.rows = round(math.sqrt(len(active_cameras)))
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self.camera_layout = [None] * (self.columns * self.rows)
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self.clear_frame()
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# remove inactive cameras from the layout
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self.camera_layout = [
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cam if cam in active_cameras else None for cam in self.camera_layout
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]
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# place the active cameras in the layout
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while len(active_cameras) > 0:
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cam = active_cameras.pop()
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if cam in self.camera_layout:
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continue
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# place camera in the first available spot in the layout
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for i in range(0, len(self.camera_layout) - 1):
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if self.camera_layout[i] is None:
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self.camera_layout[i] = cam
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break
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# calculate resolution of each position in the layout
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# if layout is changing, wipe the frame black again
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# For each camera currently tracking objects (alphabetical):
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width = self.frame_shape[1] / self.columns
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height = self.frame_shape[0] / self.rows
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# For each camera in the layout:
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# - resize the current frame and copy into the birdseye view
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# signal to birdseye process that the frame is ready to send
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self.frame[:] = frame
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return True
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def output_frames(config, video_output_queue):
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threading.current_thread().name = f"output"
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@ -170,13 +223,13 @@ def output_frames(config, video_output_queue):
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ws.environ["PATH_INFO"].endswith("birdseye")
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for ws in websocket_server.manager
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):
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birdseye_manager.update(
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if birdseye_manager.update(
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camera,
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len(current_tracked_objects),
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len(motion_boxes),
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frame_time,
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frame,
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)
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):
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converters["birdseye"].write(birdseye_manager.frame.tobytes())
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if camera in previous_frames:
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