应该是sensor板没有插紧。看一下螺丝有没有拧紧，如果不行可以寄回检查维修。

import sensor
import time
import image

Reset sensor

sensor.reset()

Sensor settings

sensor.set_contrast(3)
sensor.set_gainceiling(16)

HQVGA and GRAYSCALE are the best for face tracking.

sensor.set_framesize(sensor.HQVGA)
sensor.set_pixformat(sensor.GRAYSCALE)

Load Haar Cascade

By default this will use all stages, lower satges is faster but less accurate.

face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)
print(face_cascade)

FPS clock

clock = time.clock()

while True:
clock.tick()

# Capture snapshot
img = sensor.snapshot()

# Find objects.
# Note: Lower scale factor scales-down the image more and detects smaller objects.
# Higher threshold results in a higher detection rate, with more false positives.
objects = img.find_features(face_cascade, threshold=0.75, scale_factor=1.25)

# Draw objects
for r in objects:
    img.draw_rectangle(r)

# Print FPS.
# Note: Actual FPS is higher, streaming the FB makes it slower.
print(clock.fps())

这一行
face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)报错，OSError: [Errno 19] ENODEV。

使用星瞳回数的串口助手，使用其他串口助手不回数

import sensor, image, time,pyb

led = pyb.LED(3)
led.on()
sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.
while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.
    a = img.get_pixel(75,60)
    print("A",a,"B")

import sensor, image, time
from pyb import CAN

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.skip_frames(time = 2000)     # Wait for settings take effect.
clock = time.clock()                # Create a clock object to track the FPS.

while(True):
    clock.tick()                    # Update the FPS clock.
    img = sensor.snapshot()         # Take a picture and return the image.
    print(clock.fps())              # Note: OpenMV Cam runs about half as fast when connected
                                    # to the IDE. The FPS should increase once disconnected.

import sensor, image, time,math
import car
from pid import PID
from pyb import UART
from pyb import LED

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(True) # turn this off.
clock = time.clock() # Tracks FPS.

uart = UART(3, 9600, timeout_char=1000)
uart.init(9600, bits=8, parity=None, stop=1,timeout_char=1000)#串口通讯初始化设置

while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().  
    print("haha")

import sensor, image, time

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.

face_cascade = image.HaarCascade("frontalface", stages=25)



while(True):


    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.
    
    objects = sensor.snapshot().to_grayscale().find_features(face_cascade, threshold=0.75, scale=1.35)
   
    if objects:
        print("检测到人脸")
    
    for code in img.find_qrcodes():
        message = code.payload()
        print(message)
    
    
   

麻烦看下

是因为IDE没有接收到数据。代码里是正常采集到的。

如果想显示，可以这样：

import sensor, image, time     


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.skip_frames(time = 2000)     # Wait for settings take effect.


# 获得一帧图像

img = sensor.snapshot()

threshold = (0,100,   -128,127,	20,50)
img.binary([threshold])

img = sensor.snapshot()
while True:
    time.sleep(1)

# This code run in OpenMV4 H7 or OpenMV4 H7 Plus

import sensor, image, time, os, tf

sensor.reset()                         # Reset and initialize the sensor.
sensor.set_pixformat(sensor.GRAYSCALE)    # 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(time=2000)          # Let the camera adjust.

clock = time.clock()
while(True):
    clock.tick()
    img = sensor.snapshot().binary([(0,64)])
    for obj in tf.classify("trained.tflite", img, min_scale=1.0, scale_mul=0.5, x_overlap=0.0, y_overlap=0.0):
        output = obj.output()
        number = output.index(max(output))
        print(number)
    print(clock.fps(), "fps")

要将图片变成base64的码流，是否在sensor抓取图片之后可以直接将图片进行base64编码？

代码都是一样的，和镜头无关。

函数：https://docs.singtown.com/micropython/zh/latest/openmvcam/library/omv.sensor.html#sensor.sensor.set_auto_exposure
例子：
https://book.openmv.cc/example/21-Sensor-Control/sensor_exposure_control.html