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https://github.com/blakeblackshear/frigate.git
synced 2025-10-27 10:52:11 +01:00
use a regular subprocess for ffmpeg, refactor bounding box drawing
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blakeblackshear
Blake Blackshear
parent
2b51dc3e5b
commit
baa587028b
30
Dockerfile
30
Dockerfile
@ -1,5 +1,7 @@
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FROM ubuntu:18.04
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ARG DEVICE
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# Install packages for apt repo
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RUN apt-get -qq update && apt-get -qq install --no-install-recommends -y \
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apt-transport-https \
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@ -8,11 +10,14 @@ RUN apt-get -qq update && apt-get -qq install --no-install-recommends -y \
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wget \
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gnupg-agent \
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dirmngr \
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software-properties-common
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software-properties-common \
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&& rm -rf /var/lib/apt/lists/*
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RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys D986B59D
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COPY scripts/install_odroid_repo.sh .
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RUN echo "deb http://deb.odroid.in/5422-s bionic main" > /etc/apt/sources.list.d/odroid.list
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RUN if [ "$DEVICE" = "odroid" ]; then \
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sh /install_odroid_repo.sh; \
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fi
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RUN apt-get -qq update && apt-get -qq install --no-install-recommends -y \
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python3 \
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@ -52,10 +57,12 @@ RUN pip install -U pip \
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numpy \
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Flask \
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paho-mqtt \
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PyYAML \
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ffmpeg-python
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PyYAML
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# Download & build OpenCV
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# TODO: use multistage build to reduce image size:
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# https://medium.com/@denismakogon/pain-and-gain-running-opencv-application-with-golang-and-docker-on-alpine-3-7-435aa11c7aec
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# https://www.merixstudio.com/blog/docker-multi-stage-builds-python-development/
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RUN wget -q -P /usr/local/src/ --no-check-certificate https://github.com/opencv/opencv/archive/4.0.1.zip
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RUN cd /usr/local/src/ \
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&& unzip 4.0.1.zip \
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@ -70,14 +77,15 @@ RUN cd /usr/local/src/ \
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&& rm -rf /usr/local/src/opencv-4.0.1
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# Download and install EdgeTPU libraries for Coral
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RUN wget https://dl.google.com/coral/edgetpu_api/edgetpu_api_latest.tar.gz -O edgetpu_api.tar.gz --trust-server-names
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RUN wget https://dl.google.com/coral/edgetpu_api/edgetpu_api_latest.tar.gz -O edgetpu_api.tar.gz --trust-server-names \
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&& tar xzf edgetpu_api.tar.gz
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RUN tar xzf edgetpu_api.tar.gz \
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&& cd edgetpu_api \
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&& cp -p libedgetpu/libedgetpu_arm32.so /usr/lib/arm-linux-gnueabihf/libedgetpu.so.1.0 \
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&& ldconfig \
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&& python3 -m pip install --no-deps "$(ls edgetpu-*-py3-none-any.whl 2>/dev/null)"
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COPY scripts/install_edgetpu_api.sh edgetpu_api/install.sh
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RUN cd edgetpu_api \
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&& /bin/bash install.sh
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# Copy a python 3.6 version
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RUN cd /usr/local/lib/python3.6/dist-packages/edgetpu/swig/ \
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&& ln -s _edgetpu_cpp_wrapper.cpython-35m-arm-linux-gnueabihf.so _edgetpu_cpp_wrapper.cpython-36m-arm-linux-gnueabihf.so
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@ -89,8 +89,6 @@ class FramePrepper(threading.Thread):
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cropped_frame = self.shared_frame[self.region_y_offset:self.region_y_offset+self.region_size, self.region_x_offset:self.region_x_offset+self.region_size].copy()
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frame_time = self.frame_time.value
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# convert to RGB
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#cropped_frame_rgb = cv2.cvtColor(cropped_frame, cv2.COLOR_BGR2RGB)
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# Resize to 300x300 if needed
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if cropped_frame.shape != (300, 300, 3):
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cropped_frame = cv2.resize(cropped_frame, dsize=(300, 300), interpolation=cv2.INTER_LINEAR)
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@ -2,6 +2,7 @@ import time
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import datetime
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import threading
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import cv2
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from . util import draw_box_with_label
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class ObjectCleaner(threading.Thread):
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def __init__(self, objects_parsed, detected_objects):
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@ -79,12 +80,9 @@ class BestPersonFrame(threading.Thread):
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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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color = (255,0,0)
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cv2.rectangle(best_frame, (self.best_person['xmin'], self.best_person['ymin']),
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(self.best_person['xmax'], self.best_person['ymax']),
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color, 2)
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# convert back to BGR
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label = "{}: {}%".format(self.best_person['name'],int(self.best_person['score']*100))
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draw_box_with_label(best_frame, self.best_person['xmin'], self.best_person['ymin'],
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self.best_person['xmax'], self.best_person['ymax'], label)
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self.best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)
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@ -1,5 +1,26 @@
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import numpy as np
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import cv2
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# convert shared memory array into numpy array
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def tonumpyarray(mp_arr):
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return np.frombuffer(mp_arr.get_obj(), dtype=np.uint8)
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def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label):
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color = (255,0,0)
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cv2.rectangle(frame, (x_min, y_min),
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(x_max, y_max),
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color, 2)
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font_scale = 0.5
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font = cv2.FONT_HERSHEY_SIMPLEX
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# get the width and height of the text box
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size = cv2.getTextSize(label, font, fontScale=font_scale, thickness=2)
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text_width = size[0][0]
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text_height = size[0][1]
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line_height = text_height + size[1]
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# set the text start position
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text_offset_x = x_min
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text_offset_y = 0 if y_min < line_height else y_min - line_height
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# make the coords of the box with a small padding of two pixels
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textbox_coords = ((text_offset_x, text_offset_y), (text_offset_x + text_width + 2, text_offset_y + line_height))
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cv2.rectangle(frame, textbox_coords[0], textbox_coords[1], color, cv2.FILLED)
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cv2.putText(frame, label, (text_offset_x, text_offset_y + line_height - 2), font, fontScale=font_scale, color=(0, 0, 0), thickness=2)
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@ -5,9 +5,10 @@ import cv2
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import threading
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import ctypes
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import multiprocessing as mp
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import subprocess as sp
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import numpy as np
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import ffmpeg
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from . util import tonumpyarray
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from . util import tonumpyarray, draw_box_with_label
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from . object_detection import FramePrepper
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from . objects import ObjectCleaner, BestPersonFrame
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from . mqtt import MqttObjectPublisher
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@ -16,34 +17,29 @@ from . mqtt import MqttObjectPublisher
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def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_shape, rtsp_url):
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# convert shared memory array into numpy and shape into image array
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arr = tonumpyarray(shared_arr).reshape(frame_shape)
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frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2]
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ffmpeg_process = (
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ffmpeg
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.input(rtsp_url,
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rtsp_transport="tcp",
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stimeout=5000000,
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use_wallclock_as_timestamps=1,
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fflags="+genpts",
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avoid_negative_ts="make_zero")
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.output('pipe:', format='rawvideo', pix_fmt='rgb24')
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)
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ffmpeg_cmd = ['ffmpeg',
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'-avoid_negative_ts', 'make_zero',
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'-fflags', '+genpts',
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'-rtsp_transport', 'tcp',
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'-stimeout', '5000000',
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'-use_wallclock_as_timestamps', '1',
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'-i', rtsp_url,
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'-f', 'rawvideo',
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'-pix_fmt', 'rgb24',
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'pipe:']
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print(ffmpeg_process.compile())
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ffmpeg_process = ffmpeg_process.run_async(pipe_stdout=True)
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pipe = sp.Popen(ffmpeg_cmd, stdout = sp.PIPE, bufsize=frame_size)
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while True:
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in_bytes = ffmpeg_process.stdout.read(frame_shape[0] * frame_shape[1] * frame_shape[2])
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if not in_bytes:
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print("No bytes received. Waiting 1 second before trying again.")
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time.sleep(1)
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continue
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raw_image = pipe.stdout.read(frame_size)
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frame = (
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np
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.frombuffer(in_bytes, np.uint8)
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.frombuffer(raw_image, np.uint8)
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.reshape(frame_shape)
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)
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# Lock access and update frame
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with frame_lock:
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shared_frame_time.value = datetime.datetime.now().timestamp()
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arr[:] = frame
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@ -51,7 +47,7 @@ def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_s
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with frame_ready:
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frame_ready.notify_all()
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ffmpeg_process.wait()
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pipe.stdout.flush()
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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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@ -272,14 +268,10 @@ class Camera:
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with self.frame_lock:
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frame = self.shared_frame_np.copy()
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# convert to RGB for drawing
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#frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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# draw the bounding boxes on the screen
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for obj in detected_objects:
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color = (255,0,0)
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cv2.rectangle(frame, (obj['xmin'], obj['ymin']),
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(obj['xmax'], obj['ymax']),
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color, 2)
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label = "{}: {}%".format(obj['name'],int(obj['score']*100))
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draw_box_with_label(frame, obj['xmin'], obj['ymin'], obj['xmax'], obj['ymax'], label)
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for region in self.regions:
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color = (255,255,255)
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@ -287,7 +279,7 @@ class Camera:
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(region['x_offset']+region['size'], region['y_offset']+region['size']),
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color, 2)
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# convert back to BGR
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# convert to BGR
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frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
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return frame
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