做微商进哪个网站安全,wordpress 文章 attachment_id,wordpress 代替cms,手机商城小程序参加了一次RT-Thread的开发者大会#xff0c;相当有意思#xff0c;虽然一天奔波挺累#xff0c;但睡了半天之后简单剪了下22号的视频#xff0c;也就有时间写自己的参会笔记了。 与openEuler社区不同#xff0c;RT-Thread社区更专注于嵌入式#xff0c;与硬件厂商结合较…参加了一次RT-Thread的开发者大会相当有意思虽然一天奔波挺累但睡了半天之后简单剪了下22号的视频也就有时间写自己的参会笔记了。 与openEuler社区不同RT-Thread社区更专注于嵌入式与硬件厂商结合较为紧密。我是在openEuler的嵌入式SIG的引导下来的openEuler社区的Embedded发行版是Yocto架构为主与服务器端的发行版本并不一样。很明显在ARM-M系列的场景下是跑不了openEuler的这时RTOS实时操作系统显然更为适合这类场景正如RT-Thread开发者大会上演讲者所说RT-Thread也在做一些填补大型操作系统与硬件之间关系可以这么理解。 我们是到的最早的那一批坐了无人车到了会场外边收集着开发板边看着一家家公司布着展看着demo, 看着有意思的东西开发板、系统、小样。虽然都在说今年裁员压力大但各家公司的产品都还看起来不错。
早上是开场然后小睡了会儿主办方RTT在说社区的人更多了软件包更多了但也更为完善了更新放缓的阶段。英飞凌介绍了PSoc MCU, 瑞萨 给了几个行业应用的例子比较让我惊喜的是给了很多新能源行业的解决方案。给我不少做课设的启发如果自己的成果能解决行业问题我觉得也是挺好的方向。
下午听了场瑞萨和恩智普的边缘计算分会场的讲座。
一个在做MCU的e-AI模型迁移部署实验–强调了 MPU与MCU的界限逐渐模糊 Cheak MOTOR 电机检测
算力检测–平台HVAC风机检测13帧的视觉检测的RA8 MCU 一个在做相似的方向emmm, 没咋听全有个老哥打我电话喊我搬砖
机器学习控制器产品
对了还有一家做车载AI视觉的大宋汽车技术合作方——黑芝麻
动手实践也比较简单但挺有趣的。
现场发布的 RA8 MCU 开发板
用的 OpenMV IDE, 界面也比较简单与PR相比挺有意思的demo如下 Blog就到这了Bye 2023RT-Thread开发者大会。
这里是用到的代码# Fast Linear Regression Example
#
# This example shows off how to use the get_regression() method on your OpenMV Cam
# to get the linear regression of a ROI. Using this method you can easily build
# a robot which can track lines which all point in the same general direction
# but are not actually connected. Use find_blobs() on lines that are nicely
# connected for better filtering options and control.
#
# This is called the fast linear regression because we use the least-squares
# method to fit the line. However, this method is NOT GOOD FOR ANY images that
# have a lot (or really any) outlier points which corrupt the line fit...import sensor
import timeTHRESHOLD (0, 100) # Grayscale threshold for dark things.
BINARY_VISIBLE True # Binary pass first to see what linear regression is running on.sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time2000)
clock time.clock()while True:clock.tick()img sensor.snapshot().binary([THRESHOLD]) if BINARY_VISIBLE else sensor.snapshot()# Returns a line object similar to line objects returned by find_lines() and# find_line_segments(). You have x1(), y1(), x2(), y2(), length(),# theta() (rotation in degrees), rho(), and magnitude().## magnitude() represents how well the linear regression worked. It goes from# (0, INF] where 0 is returned for a circle. The more linear the# scene is the higher the magnitude.line img.get_regression([(255, 255) if BINARY_VISIBLE else THRESHOLD])print(FPS %f, mag %s % (clock.fps(), str(line.magnitude()) if (line) else N/A))# About negative rho values:
#
# A [theta0:-rho] tuple is the same as [theta180:rho].
# Automatic RGB565 Color Tracking Example
#
# This example shows off single color automatic RGB565 color tracking using the OpenMV Cam.import sensor
import timeprint(请勿在相机前放置任何物品)sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time2000)
sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False) # must be turned off for color tracking
clock time.clock()# Capture the color thresholds for whatever was in the center of the image.
r [(320 // 2) - (50 // 2), (240 // 2) - (50 // 2), 50, 50] # 50x50 center of QVGA.print(将要跟踪的物体放在相机前面的框中
)
print(确保您要追踪的物体的颜色完全被框住
)
for i in range(60):img sensor.snapshot()img.draw_rectangle(r)print(开始学习颜色 )
threshold [50, 50, 0, 0, 0, 0] # Middle L, A, B values.
for i in range(60):img sensor.snapshot()hist img.get_histogram(roir)lo hist.get_percentile(0.01) # Get the CDF of the histogram at the 1% range (ADJUST AS NECESSARY)!hi hist.get_percentile(0.99) # Get the CDF of the histogram at the 99% range (ADJUST AS NECESSARY)!# Average in percentile values.threshold[0] (threshold[0] lo.l_value()) // 2threshold[1] (threshold[1] hi.l_value()) // 2threshold[2] (threshold[2] lo.a_value()) // 2threshold[3] (threshold[3] hi.a_value()) // 2threshold[4] (threshold[4] lo.b_value()) // 2threshold[5] (threshold[5] hi.b_value()) // 2for blob in img.find_blobs([threshold], pixels_threshold100, area_threshold100, mergeTrue, margin10):img.draw_rectangle(blob.rect())img.draw_cross(blob.cx(), blob.cy())img.draw_rectangle(r)print(Thresholds learned...)
print(Tracking colors...)while True:clock.tick()img sensor.snapshot()for blob in img.find_blobs([threshold], pixels_threshold100, area_threshold100, mergeTrue, margin10):img.draw_rectangle(blob.rect())img.draw_cross(blob.cx(), blob.cy())print(clock.fps())
RA8 MCU开发板如果大家感兴趣的话我就专门出一期看看有没有人想看超过10票就发嘿嘿。
