硬件购买以及注意点
购买硬件之后在网卡后面有个短路帽要加上，否则无法开机。
系统安装
nvidia jetson nano系统安装在SD卡中，请预先准备一个32G的SD卡
系统安装步骤请参考官网
Getting Started With Jetson Nano Developer Kit | NVIDIA Developer
注意：烧录完成会弹出好多个窗口，请求格式化，此处一定要点 取消 不要格式化，因为这是软件在为系统分盘。
开发前准备
检查opencv是否安装
命令行：opencv_version
输出：4.1.1
检查显卡驱动和cuda是否安装
命令行：nvcc -V
输出：bash: nvcc command not found
解决：驱动其实已经安装了，我们需要加入环境变量
sudo vim ~./bashrc
或者也可以直接到本地电脑的Home文件夹中找到.bashrc文件，直接打开文件，在文件的最后位置添加上三行命令。（若进到Home文件夹没看有.bashrc文件，则点击一下Ctrl + H就可以显示出.bashrc）
在文件最后添加
export PATH=/usr/local/cuda-10.2/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
export CUDA_HOME=/usr/local/cuda
设置完成后可以正常看到nvcc -V 的信息
安装jtop以便查看设备信息
sudo apt-get install git cmake
sudo apt-get install python3-dev
sudo apt-get install libhdf5-serial-dev hdf5-tools
sudo apt-get install libatlas-base-dev gfortran
sudo apt-get install python3-pip
sudo -H pip3 install -U jetson-stats
sudo systemctl restart jetson_stats.service
reboot
jtop
安装opencv
sys Update
sudo apt-get update
sudo apt-get full-upgrade
sudo add-apt-repository "deb http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ xenial main multiverse restricted universe"
sudo apt update
set nvcc
sudo vim ~/.bashrc
export CUDA_HOME=/usr/local/cuda-10.2
export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64:$LD_LIBRARY_PATH
export PATH=/usr/local/cuda-10.2/bin:$PATH
source ~/.bashrc
# test
nvcc -V
安装OpenCV with CUDA
sudo apt-get install build-essential
sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
sudo apt-get install python3-dev python3-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev
sudo apt-get install pkg-config
sudo apt-get install opencv3-pip
unzip opencv4.6-contrib-xfture
build> cmake
-D CMAKE_INSTALL_PREFIX=/usr/local
-D CMAKE_BUILD_TYPE=Release
-D OPENCV_EXTRA_MODULES_PATH=../opencv_contrib/modules
-D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-10.2
-D CUDA_ARCH_BIN=5.3
-D CUDA_ARCH_PTX=""
-D BUILD_PNG=OFF
-D BUILD_TIFF=OFF
-D BUILD_TBB=OFF
-D BUILD_JPEG=OFF
-D BUILD_JASPER=OFF
-D BUILD_ZLIB=OFF
-D BUILD_EXAMPLES=ON
-D BUILD_opencv_java=OFF
-D BUILD_opencv_python2=OFF
-D BUILD_opencv_python3=ON
-D ENABLE_PRECOMPILED_HEADERS=OFF
-D WITH_OPENCL=OFF
-D WITH_OPENMP=OFF
-D WITH_FFMPEG=ON
-D WITH_GSTREAMER=OFF
-D WITH_GSTREAMER_0_10=OFF
-D WITH_CUDA=ON
-D WITH_GTK=ON
-D WITH_VTK=OFF
-D WITH_TBB=ON
-D PYTHON_DEFAULT_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)")
-D PYTHON3_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)")
-D PYTHON3_NUMPY_INCLUDE_DIRS=$(python3 -c "import numpy; print (numpy.get_include())")
-D PYTHON3_PACKAGES_PATH=$(python3 -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())")
-D WITH_1394=OFF
-D WITH_OPENEXR=OFF
-D INSTALL_C_EXAMPLES=ON -D INSTALL_TESTS=OFF
..
build> make -j4
build> sudo make install
build> sudo python3 setup.py install
if "sudo python3 setup.py install " error :
pip3 install setuptools
pip3 install --upgrade setuptools
pip3 install --upgrade pip
do sudo python3 setup.py install again!
pip3 install Pillow
pip3 install pygame -i https://pypi.tuna.tsinghua.edu.cn/simple/
CameraCall.py
# encoding: utf-8
import cv2 as cv
import subprocess
class CameraCallTool(object):
cap = None
def __init__(self, width, height, CamIndex):
print(f'Init Camera Tool!')
if CamIndex == -1:
self.CallCameraOnBoard(width, height)
elif CamIndex == 0:
self.CallCameraOnCSI(width, height)
else:
print('no usb camera!')
def CallCameraOnCSI(self, width, height):
self.cap = cv.VideoCapture(0) #设置摄像头 0是默认的摄像头 如果你有多个摄像头的话呢，可以设置1,2,3....
self.cap.set(cv.CAP_PROP_FRAME_WIDTH, width)
self.cap.set(cv.CAP_PROP_FRAME_HEIGHT, height)
self.cap.set(cv.CAP_PROP_EXPOSURE, 0.1)
def Test(self):
print('CameraCallTool Test')
def CameraStatus(self):
return self.cap.isOpened()
def CallCameraOnBoard(self, width, height):
gst_elements = str(subprocess.check_output('gst-inspect-1.0'))
if 'nvcamerasrc' in gst_elements:
# On versions of L4T prior to 28.1, add 'flip-method=2' into gst_str
gst_str = ('nvcamerasrc ! '
'video/x-raw(memory:NVMM), '
'width=(int)2592, height=(int)1458, '
'format=(string)I420, framerate=(fraction)30/1 ! '
'nvvidconv ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)BGRx ! '
'videoconvert ! appsink').format(width, height)
elif 'nvarguscamerasrc' in gst_elements:
gst_str = ('nvarguscamerasrc ! '
'video/x-raw(memory:NVMM), '
'width=(int)1920, height=(int)1080, '
'format=(string)NV12, framerate=(fraction)30/1 ! '
'nvvidconv flip-method=2 ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)BGRx ! '
'videoconvert ! appsink').format(width, height)
else:
raise RuntimeError('onboard camera source not found!')
# return cv.VideoCapture(gst_str, cv.CAP_GSTREAMER)
self.cap = cv.VideoCapture(gst_str, cv.CAP_GSTREAMER)
def GetOneFrame(self):
if self.cap.isOpened():
ret, frame = self.cap.read()
if ret is True:
# 摄像头是和人对立的，将图像左右调换回来正常显示。
frame = cv.flip(frame, 1)
frame = cv.flip(frame, 0)
return frame
else:
return None
else:
return None
def __del__(self):
if self.cap is not None:
self.cap.release()
print('CameraCallTool del')
DnnClass.py
# encoding: utf-8
import numpy as np
import cv2 as cv
import os
import time
class MyDnn(object):
# YOLO文件路径 G:\vs2017Project\yolov2-tiny-voc
yolo_dir = './yolov3-tiny'
# 过滤弱检测的最小概率
CONFIDENCE = 0.5
# 非最大值抑制阈值
THRESHOLD = 0.4
def __init__(self):
print('import Dnn Tool Calss!')
# YOLO文件路径
self.yolo_dir_name = self.yolo_dir
# 权重文件
self.weightsPath = os.path.join(self.yolo_dir, 'yolov3.weights')
# 配置文件
self.configPath = os.path.join(self.yolo_dir, 'yolov3.cfg')
# label名称
self.labelsPath = os.path.join(self.yolo_dir_name, 'coco.names')
# 加载网络、配置权重
self.net = cv.dnn.readNetFromDarknet(self.configPath, self.weightsPath)
# intel gpu
# self.net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
# self.net.setPreferableTarget(cv.dnn.DNN_TARGET_OPENCL)
# cpu
# self.net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
# self.net.setPreferableTarget(cv.dnn.DNN_TARGET_CPU)
# nvidia gpu
self.net.setPreferableBackend(cv.dnn.DNN_BACKEND_CUDA)
self.net.setPreferableTarget(cv.dnn.DNN_TARGET_CUDA)
print("[INFO] loading YOLO from disk...") # # 可以打印下信息
def importTest(self):
print('dnn import test!')
def DecodeImage(self, img):
start = time.time()
# 加载图片、转为blob格式、送入网络输入层
# img = imagePath
# net需要的输入是blob格式的，用blobFromImage这个函数来转格式
blobImg = cv.dnn.blobFromImage(img, 1.0/255.0, (416, 416), None, True, False)
# 调用setInput函数将图片送入输入层
self.net.setInput(blobImg)
# 前面的yolov3架构也讲了，yolo在每个scale都有输出，outInfo是每个scale的名字信息，供net.forward使用
outInfo = self.net.getUnconnectedOutLayersNames()
# 得到各个输出层的、各个检测框等信息，是二维结构。
layerOutputs = self.net.forward(outInfo)
end = time.time()
print("[INFO] YOLO took {:.6f} seconds".format(end - start))
# 拿到图片尺寸
(H, W) = img.shape[:2]
# 过滤layerOutputs
# layerOutputs的第1维的元素内容: [center_x, center_y, width, height, objectness, N-class score data]
# 过滤后的结果放入：
# 所有边界框（各层结果放一起）
boxes = []
# 所有置信度
confidences = []
# 所有分类ID
classIDs = []
# # 1）过滤掉置信度低的框框
# 各个输出层
for out in layerOutputs:
# 各个框框
for detection in out:
# 拿到置信度
# 各个类别的置信度
scores = detection[5:]
# 最高置信度的id即为分类id
classID = np.argmax(scores)
# 拿到置信度
confidence = scores[classID]
# 根据置信度筛查
if confidence > self.CONFIDENCE:
# 将边界框放会图片尺寸
box = detection[0:4] * np.array([W, H, W, H])
(centerX, centerY, width, height) = box.astype("int")
x = int(centerX - (width / 2))
y = int(centerY - (height / 2))
boxes.append([x, y, int(width), int(height)]) # 框
confidences.append(float(confidence)) # 置信度
classIDs.append(classID) # 分类ID
# # 2）应用非最大值抑制(non-maxima suppression，nms)进一步筛掉
# boxes中，保留的box的索引index存入idxs
idxs = cv.dnn.NMSBoxes(boxes, confidences, self.CONFIDENCE, self.THRESHOLD)
# 得到labels列表
with open(self.labelsPath, 'rt') as f:
labels = f.read().rstrip('\n').split('\n')
np.random.seed(42)
# 框框显示颜色，每一类有不同的颜色，每种颜色都是由RGB三个值组成的，所以size为(len(labels), 3)
COLORS = np.random.randint(0, 255, size=(len(labels), 3), dtype="uint8")
if len(idxs) > 0:
# alarm pic
for i in idxs.flatten(): # indxs是二维的，第0维是输出层，所以这里把它展平成1维
(x, y) = (boxes[i][0], boxes[i][1])
(w, h) = (boxes[i][2], boxes[i][3])
color = [int(c) for c in COLORS[classIDs[i]]]
# 线条粗细为2px
cv.rectangle(img, (x, y), (x+w, y+h), color, 2)
cv.rectangle(img, (x, y), (x+w, y+h), color, 2)
# 线条粗细为2px
text = "{}: {:.4f}".format(labels[classIDs[i]], confidences[i])
# cv.FONT_HERSHEY_SIMPLEX字体风格、0.5字体大小、粗细2px
cv.putText(img, text, (x, y-5), cv.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
print('alarm pic!')
cv.imshow('decode', img)
return img
else:
# normal pic
print('normal pic!')
return None
DnnMain.py
# encoding: utf-8
import cv2 as cv
from DnnClass import MyDnn
from CameraCall import CameraCallTool
import pygame
from PIL import Image, ImageDraw, ImageFont
import threading
import subprocess
def LoadMusic():
pygame.mixer.init()
pygame.mixer.music.load('./audio/succ.wav')
pygame.mixer.music.set_volume(0.5)
def PlaySuccess():
pygame.mixer.music.play()
def DrawTextOnImage(img, text1, text2, left, top, textColor=(0,255,0), textSize=20):
if(isinstance(img, np.ndarray)):
img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
# create a draw to draw text
draw = ImageDraw.Draw(img)
fontstyle = ImageFont.truetype('./font/simsun.ttc', textSize, encoding='utf-8')
draw.text((left,top), text1, textColor, font=fontstyle)
draw.text((left,int(top + textSize + 2)), text2, textColor, font=fontstyle)
return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)
def CallCameraOnBoard(width, height):
gst_elements = str(subprocess.check_output('gst-inspect-1.0'))
if 'nvcamerasrc' in gst_elements:
# On versions of L4T prior to 28.1, add 'flip-method=2' into gst_str
gst_str = ('nvcamerasrc ! '
'video/x-raw(memory:NVMM), '
'width=(int)2592, height=(int)1458, '
'format=(string)I420, framerate=(fraction)30/1 ! '
'nvvidconv ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)BGRx ! '
'videoconvert ! appsink').format(width, height)
elif 'nvarguscamerasrc' in gst_elements:
gst_str = ('nvarguscamerasrc ! '
'video/x-raw(memory:NVMM), '
'width=(int)1920, height=(int)1080, '
'format=(string)NV12, framerate=(fraction)30/1 ! '
'nvvidconv flip-method=2 ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)BGRx ! '
'videoconvert ! appsink').format(width, height)
else:
raise RuntimeError('onboard camera source not found!')
return cv.VideoCapture(gst_str, cv.CAP_GSTREAMER)
if __name__ == "__main__":
print('camera onboard')
DnnTool = MyDnn()
cameraCallTool = CameraCallTool(1024, 768, 0)
t = 0
try:
while cameraCallTool.CameraStatus():
CameraFrame = cameraCallTool.GetOneFrame()
if CameraFrame is not None:
cv.imshow('Video', CameraFrame)
if t == 0 or t.is_alive() is False:
# image_np = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
t = threading.Thread(target=DnnTool.DecodeImage, args=(CameraFrame, ))
t.start()
#判断退出的条件 当按下'Q'键的时候呢，就退出
c = cv.waitKey(1)
# 如果按下q 就截图保存并退出
if c == ord('q'):
saveFile = "Capture.jpg" # 带有中文的保存文件路径
img_write = cv.imencode(".jpg", CameraFrame)[1].tofile(saveFile)
break
except:
print('Camera Show Exception!')
finally:
del cameraCallTool
cv.destroyAllWindows()
lost : audo font yolov3-tiny
本文内容由网友自发贡献，版权归原作者所有，本站不承担相应法律责任。如您发现有涉嫌抄袭侵权的内容，请联系:hwhale#tublm.com(使用前将#替换为@)
