运行在树莓派中的 scratch3-adapter opencv 插件
种瓜
·
2018-12-27
·
via 夜行人
文章目录
提醒
暂未升级到 3.0 ， 正在进行中…
我们在上一篇文章里介绍了如何制作运行在树莓派中的scratch3-adapter tensorflow插件。
tensorflow models的使用非常繁琐。本文介绍如何使用OpenCV的dnn模块调用TesorFlow训练的模型，实现物体检测。
配置要简单的多。
这部分的操作与上篇文章相同.
安装依赖
1
2
3
4
5
6
7
|
sudo apt-get install libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev
sudo apt-get install libxvidcore-dev libx264-dev
sudo apt install libatlas-base-dev
# sudo apt-get install qt4-dev-tools
# 如果失败 则: sudo apt-get install qt4-dev-tools --fix-missing
pip3 install opencv-python imutils pyzmq --user
|
下载物体检测程序(包含模型)
1
2
|
cd ~/scratch3_adapter
git clone https://github.com/wwj718/ExploreOpencvDnn
|
构建scratch3-adapter插件
在~/scratch3_adapter/extensions/构建extension_opencv.py:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
|
import time
import zmq
from zmq import Context
import subprocess
import pathlib
import platform
from scratch3_adapter.core_extension import Extension
from scratch3_adapter import settings
class OpencvExtension(Extension):
def __init__(self):
name = type(self).__name__ # class name
super().__init__(name)
def run(self):
# REP
port = 38780
context = Context.instance()
socket = context.socket(zmq.REP)
socket.bind("tcp://*:%s" % port)
# Object_detection_for_adapter.py 依赖于shell中的变量，所以需要在命令行里启动
# ~/scratch3_adapter目录
scratch3_adapter_dir = pathlib.Path.home() / "scratch3_adapter"
script = "{}/ExploreOpencvDnn/main_for_adapter.py".format(scratch3_adapter_dir)
if (platform.system() == "Darwin"):
# which python3
python = "/usr/local/bin/python3"
if platform.system() == "Windows":
python = "python"
if platform.system() == "Linux":
python = "/usr/bin/python3"
cmd = [python, script]
tf = subprocess.Popen(cmd)
while self._running:
tf_class = socket.recv_json().get("class")
socket.send_json({"status":"200"})
# 发往scratch3.0中的eim积木
self.publish({"topic": "eim", "message": tf_class})
# release socket
tf.terminate()
tf.wait()
socket.close()
context.term()
export = OpencvExtension
|
搞定.
双击运行scratch3-adapter. 之后勾选extension_opencv插件就行。
提醒
scratch3-adapter opencv 插件目前支持树莓派、macOS、Windows.
运行在笔记本上，处理速度要快很多。
参考
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。
