@iv2r

# 保存视频例程
#
# 注意：您将需要SD卡来运行此演示。
#
# 您可以使用OpenMV Cam来录制mjpeg文件。 您可以为记录器对象提供JPEG帧
# 或RGB565 /灰度帧。 一旦你完成了一个Mjpeg文件的录制，你可以使用VLC
# 来播放它。 如果你在Ubuntu上，那么内置的视频播放器也可以工作。
import sensor, image, time, mjpeg, pyb

RED_LED_PIN = 1
BLUE_LED_PIN = 3

sensor.reset() # 初始化sensor

sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
#设置图像色彩格式，有RGB565色彩图和GRAYSCALE灰度图两种

sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
#设置图像像素大小

sensor.skip_frames(time = 2000) # 让新的设置生效
clock = time.clock() # 跟踪FPS帧率

pyb.LED(RED_LED_PIN).on()
sensor.skip_frames(30) # 给用户一个时间来准备

pyb.LED(RED_LED_PIN).off()
pyb.LED(BLUE_LED_PIN).on()

m = mjpeg.Mjpeg("example.mjpeg")
#mjpeg.Mjpeg(filename, width=Auto, height=Auto)创建一个mjpeg对象，
#filename为保存mjpeg动图的文件路径

print("You're on camera!")
for i in range(200):
    clock.tick()
    m.add_frame(sensor.snapshot())
    #mjpeg.add_frame(image, quality=50)，向mjpeg视频中中添加图片，
    #quality为视频压缩质量。
    print(clock.fps())

m.close(clock.fps())
pyb.LED(BLUE_LED_PIN).off()
print("Done! Reset the camera to see the saved recording.")![0_1678883849044_e1c4853c701314f4d86a6c9d72702ed.png](https://fcdn.singtown.com/c0e7f99a-0f65-48dd-82d6-5de5f967c161.png) 

如何提高训练的模型的正确率呢？增大数据集吗

回复: 如何加延时函数

当openmv识别到色块时，需要让它一秒钟之内不发送数据，请问怎么解决，好像加上延迟函数它就跟睡死了，请问怎么解决呢？谢谢

import sensor, image, pyb
import time, os, tf, math, uos, gc
from pyb import UART,LED

LED(3).on()

sensor.reset()                         # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565)    # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA)      # Set frame size to QVGA (320x240)
sensor.set_windowing((240, 240))       # Set 240x240 window.
sensor.skip_frames(30)          # Let the camera adjust.

uart = UART(3, 115200)
uart.init(115200, bits=8, parity=None, stop=1)
def send_data(data1):
    global uart
    data = bytearray([0xb3,0xb3,data1,0x5b])
    uart.write(data)


net = None
labels = None
min_confidence = 0.5

try:
    # load the model, alloc the model file on the heap if we have at least 64K free after loading
    net = tf.load("trained.tflite", load_to_fb=uos.stat('trained.tflite')[6] > (gc.mem_free() - (64*1024)))
except Exception as e:
    raise Exception('Failed to load "trained.tflite", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')

try:
    labels = [line.rstrip('\n') for line in open("labels.txt")]
except Exception as e:
    raise Exception('Failed to load "labels.txt", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')

colors = [ # Add more colors if you are detecting more than 7 types of classes at once.
    (255,   0,   0),
    (  0, 255,   0),
    (255, 255,   0),
    (  0,   0, 255),
    (255,   0, 255),
    (  0, 255, 255),
    (255, 255, 255),
]

clock = time.clock()
while(True):
    clock.tick()
    row_data=0 # 0 正常行走，1 停止，2 等待

    img = sensor.snapshot()

    # detect() returns all objects found in the image (splitted out per class already)
    # we skip class index 0, as that is the background, and then draw circles of the center
    # of our objects

    for i, detection_list in enumerate(net.detect(img, thresholds=[(math.ceil(min_confidence * 255), 255)])):
        if (i == 0): continue # background class
        if (len(detection_list) == 0): continue # no detections for this class?])
        if labels[i] == 's':
            row_data = 1
            print('s')
            pyb.delay(1000)
            send_data(row_data)
        if labels[i] == 'w':
            row_data = 2
            print('w')
            pyb.delay(1000)
            send_data(row_data)
        else:
            print(0)
            send_data(row_data)
    #print(row_data)

openmv4巡线的程序把固定阈值更改为自适应后巡线，有时转弯转不过来，好像就是看见弯道也没反应，请问是算力不够吗？谢谢。

import sensor, image, math
from pyb import UART,LED

LED(3).on()

uart = UART(3, 115200)
uart.init(115200, bits=8, parity=None, stop=1)
def send_data(data1,data2,data3):
    global uart
    data = bytearray([0xb3,0xb3,data1,data2,data3,0x5b])
    uart.write(data)


ROIS = [
      (0, 0, 128, 40, 0.2),
      (0, 40, 128, 40, 0.4),
      (0, 80, 128, 40, 0.6)
     ]
range_stop = [400,100,70]
range_wait = 500

weight_sum = 0
for r in ROIS: weight_sum += r[4]

sensor.reset()
sensor.set_contrast(1)
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA2)
sensor.set_brightness(10)
sensor.skip_frames(30)
sensor.set_auto_whitebal(False)
sensor.set_vflip(False)
sensor.set_hmirror(False)

def find_max(blobs):
    max_size=[0,0]
    max_ID=[-1,-1]
    for i in range(len(blobs)):
        if blobs[i].pixels()>max_size[0]:
            max_ID[1]=max_ID[0]
            max_size[1]=max_size[0]
            max_ID[0]=i
            max_size[0]=blobs[i].pixels()
        elif blobs[i].pixels()>max_size[1]:
            max_ID[1]=i
            max_size[1]=blobs[i].pixels()
    return max_ID

def degrees(radians):
    return (180 * radians) / math.pi

#def stop1():


def car_run():
    centroid_sum = [0,0]
    left_center=[-1,-1,-1]
    right_center=[-1,-1,-1]
    flag_cross=0
    flag_wait = [0,0]
    flag_stop = [0,0]

    for r in range(3):
        blobs = img.find_blobs([(0, l), (-128, a),(-128, b)], roi=ROIS[r][0:4],merge=True,area_threshold=200,margin=3,pixel_threshold=200)
        if blobs:
            stop_flag = flag_stop[0]
            max_ID=[-1,-1]
            max_ID=find_max(blobs)
            img.draw_rectangle(blobs[max_ID[0]].rect(),50)
            img.draw_cross(blobs[max_ID[0]].cx(),blobs[max_ID[0]].cy(),50)
            if max_ID[1]!=-1:
                flag_cross=1 #有岔路口
                img.draw_rectangle(blobs[max_ID[1]].rect(),50)
                img.draw_cross(blobs[max_ID[1]].cx(),blobs[max_ID[1]].cy(),50)
                if blobs[max_ID[0]].cx()<blobs[max_ID[1]].cx():
                    left_center[r]=blobs[max_ID[0]].cx()
                    right_center[r]=blobs[max_ID[1]].cx()
                else:
                    left_center[r]=blobs[max_ID[1]].cx()
                    right_center[r]=blobs[max_ID[0]].cx()
            else:
                flag_cross=0
                if blobs[max_ID[0]].pixels()>range_wait:
                    flag_wait[0]+=1
                elif blobs[max_ID[0]].pixels()>range_stop[r]:
                    flag_stop[0]=r+1
                left_center[r]=right_center[r]=blobs[max_ID[0]].cx()
            centroid_sum[0] += left_center[r] * ROIS[r][4]
            centroid_sum[1] += right_center[r] * ROIS[r][4]
            if stop_flag == 3 and flag_stop[0] == 2:
                flag_stop[1] = 1
            else:
                 flag_stop[1] = 0

    center_pos =[0,0]
    center_pos[0] = (centroid_sum[0] / weight_sum)
    center_pos[1] = (centroid_sum[1] / weight_sum)
    deflection_angle = [0,0]
    deflection_angle[0] = -math.atan((center_pos[0]-64)/80)
    deflection_angle[1] = -math.atan((center_pos[1]-64)/80)
    deflection_angle[0] = math.degrees(deflection_angle[0])
    deflection_angle[1] = math.degrees(deflection_angle[1])
    if flag_wait[0] >= 2:
        flag_wait[1] = 1
    else:
        flag_wait[1] = 0
    if center_pos[0]==center_pos[1]==0:
        deflection_angle[1]=deflection_angle[0]=0
    A=[int(deflection_angle[0]),int(deflection_angle[1]),flag_stop[1],flag_wait[1]] #1等待
    return A


while(True):
    cross = 1
    flag = 1
    if(uart.any()):
        flag = uart.readchar()
        if flag == 1:
            cross = 1
        if flag == 2:
            cross = 1
        if flag == 3:
            cross = 1
        if flag == 6:
            cross = 1
        if flag == 7:
            cross = 0
        if flag == 4:
            cross = 1
    else:
        cross = 1

    img = sensor.snapshot().lens_corr(strength = 0.5, zoom = 1.0)
    img.bilateral(3,color_sigma=0.1,space_sigma=0.1)#采用双边滤波
    img.gaussian(3, unsharp=True,)#图像消除锐化
    histogram = img.get_histogram()
    THRESHOLD = histogram.get_threshold()
    l  = THRESHOLD .l_value()
    a = THRESHOLD .a_value()
    b = THRESHOLD .b_value()
    print(THRESHOLD)
    img.binary([(0, l), (-128, a),(-128, b)])

    row_data=[0,0,0,0]
    row_data[0],row_data[1],row_data[2],row_data[3]=car_run()
    if cross == 0:
        if row_data[0] < -4:
            send_data(-4,row_data[2],row_data[3])
        if -4<= row_data[0] < 0:
            send_data(row_data[0],row_data[2],row_data[3])
        if 0 <= row_data[0] <= 3:
            send_data(0,row_data[2],row_data[3])
        if row_data[0] >3:
            send_data(row_data[0],row_data[2],row_data[3])
    if cross == 1:
        if row_data[1] < -5:
            send_data(-5,row_data[2],row_data[3])
        if -5<= row_data[1] < 0:
            send_data(row_data[1],row_data[2],row_data[3])
        if 0 <= row_data[1] <= 3:
            send_data(0,row_data[2],row_data[3])
        if row_data[1] >3:
            send_data(row_data[1],row_data[2],row_data[3])

lcd屏幕显示的区域可以设置吗？怎么设置让它显示摄像头中间区域？