# LetNet识别数字演示程序
import sensor, image, time, os, nn
sensor.reset() # 复位、初始化摄像头
sensor.set_contrast(3) # 设置对比度
sensor.set_pixformat(sensor.GRAYSCALE) # 设置像素格式 RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA) # 设置分辨率 QVGA (320x240)
sensor.set_windowing((128, 128)) # 设置 128x128 窗口
sensor.skip_frames(time=100) # 设置跳过时间
sensor.set_auto_gain(False) # 禁用自动增益
sensor.set_auto_exposure(False) # 禁用自动曝光
# 导入lenet模型
net = nn.load('/lenet.network')
labels = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']# 数字存放
clock = time.clock() # 创建时钟跟踪帧率
while(True):
clock.tick() # 更新帧率时钟
img = sensor.snapshot() # 拍照一张
out = net.forward(img.copy().binary([(150, 255)], invert=True)) #转换为二进制格式
max_idx = out.index(max(out)) # 最大准确度
score = int(out[max_idx]*100) # 小数*100,两位整数
if (score < 60): # 60%以上认为识别成功
score_str = "Sorry!" # 不成功提示放到字符串
else:
score_str = "%s:%d%% "%(labels[max_idx], score) # 识别的数字和准确度放到字符串
img.draw_string(0, 0, score_str)# 图片上显示字符串
print("Number:",score_str)# 终端显示
#print(score_str)
#print(clock.fps()) # Note: OpenMV Cam runs about half as fast when connected
# to the IDE. The FPS should increase once disconnected.
Z
zh3i 发布的帖子
-
使用lenet数字识别时,提示没有nn模块,怎么解决?