vVc20 Object Detect - 20分类

import sensor, image, time, lcd
from maix import KPU
import gc

lcd.init()                          # 初始化LCD显示屏
sensor.reset()                      # 复位并初始化摄像头
sensor.set_pixformat(sensor.RGB565) # 设置摄像头输出格式为 RGB565
sensor.set_framesize(sensor.QVGA)   # 设置摄像头输出大小为 QVGA (320x240)
sensor.skip_frames(time = 1000)     # 等待摄像头稳定
clock = time.clock()                # 创建一个clock对象，用来计算帧率

#检测模型需要320*256图输入，这里初始化一个image
od_img = image.Image(size=(320,256))

obj_name = ("aeroplane","bicycle", "bird","boat","bottle","bus","car","cat","chair","cow","diningtable", "dog","horse", "motorbike","person","pottedplant", "sheep","sofa", "train", "tvmonitor")
anchor = (1.3221, 1.73145, 3.19275, 4.00944, 5.05587, 8.09892, 9.47112, 4.84053, 11.2364, 10.0071)
# 创建一个kpu对象
kpu = KPU()
print("ready load model")
# 加载模型
#kpu.load_kmodel(0x300000, 1536936)
kpu.load_kmodel("/sd/KPU/voc20_object_detect/voc20_detect.kmodel")
# yolo2初始化
kpu.init_yolo2(anchor, anchor_num=5, img_w=320, img_h=240, net_w=320 , net_h=256 ,layer_w=10 ,layer_h=8, threshold=0.5, nms_value=0.2, classes=20)

i = 0
while True:
    i += 1
    print("cnt :", i)
    clock.tick()                        # 更新计算帧率的clock
    img = sensor.snapshot()             # 拍照，获取一张图像
    a = od_img.draw_image(img, 0,0)     # 将img图像写到od_img图像的坐标（0,0）位置处
    od_img.pix_to_ai()                  # 对rgb565的image生成ai运算需要的r8g8b8格式存储
    kpu.run_with_output(od_img)         # 对输入图像进行kpu运算
    dect = kpu.regionlayer_yolo2()      # yolo2后处理
    fps = clock.fps()                   # 获取帧率

    # 画出框并显示物体类别
    if len(dect) > 0:
        print("dect:",dect)
        for l in dect :
            a = img.draw_rectangle(l[0],l[1],l[2],l[3], color=(0, 255, 0))
            a = img.draw_string(l[0],l[1], obj_name[l[4]], color=(0, 255, 0), scale=1.5)

    a = img.draw_string(0, 0, "%2.1ffps" %(fps), color=(0, 60, 128), scale=1.0)
    lcd.display(img)
    gc.collect()

# 创建的kpu对象去初始化，释放模型内存
kpu.deinit()