# Untitled - By: nian0 - 周一 11月 20 2023 import sensor,image,lcd,time import KPU as kpu import gc #摄像头初始化 sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QVGA) sensor.set_vflip(1) #摄像头后置方式 lcd.init() #LCD初始化 clock = time.clock() #模型分类,按照20class顺序 #classes = ['light'] classes = ['red', 'green', 'yellow', 'light'] # 从SD加载模型卡上。将kmodel文件通过读卡器拷贝到SD卡。 task = kpu.load("/sd/model-95325.kmodel") #模型SD卡上 #网络参数 #anchors = [0.72, 0.88, 0.81, 2.56, 0.91, 1.0, 0.66, 0.72, 1.03, 1.16] anchor = (1.0, 1.13, 0.75, 0.84, 0.72, 2.41, 1.13, 3.81, 0.88, 2.72) #初始化yolo2网络,识别可信概率为0.7(70%) a = kpu.init_yolo2(task, 0.7, 0.3, 5, anchor) while(True): gc.collect() # 内存回收 clock.tick() img = sensor.snapshot() img = img.resize(224, 224) ## 首先获取图像的宽度和高度 #w = img.width() #h = img.height() ## 计算中心截取区域的左上角坐标 #x = (w - 224) // 2 #y = (h - 224) // 2 ## 使用图像对象的 crop 方法进行截取 #img = img.crop((x, y, 224, 224)) #print("sd") img.save("/sd/example.jpg") #print("23rwwfd") img.pix_to_ai() # 将图像数据从标准的像素格式转换为 KPU 可以处理的格式 t = time.ticks_ms() code = kpu.run_yolo2(task, img) #运行yolo2网络 t = time.ticks_ms() - t #if code: #for i in code: #a=img.draw_rectangle(i.rect()) #a = lcd.display(img) #print(classes[i.classid()]) #lcd.draw_string(i.x(), i.y(), classes[i.classid()], lcd.RED, lcd.WHITE) #lcd.draw_string(i.x(), i.y()+12, '%f1.3'%i.value(), lcd.RED, lcd.WHITE) print(code) if code: for obj in code: pos = obj.rect() print(classes[obj.classid()]) img.draw_rectangle(pos) img.draw_string(pos[0], pos[1], "%s : %.2f" %(classes[obj.classid()], obj.value()), scale=2, color=(255, 0, 0)) #comm.send_detect_result(code, classes) #img.draw_string(0, 200, "t:%dms" %(t), scale=2, color=(255, 0, 0)) a = lcd.display(img) else: a = lcd.display(img) #print(clock.fps())#打印FPS