80 lines
2.5 KiB
Python
80 lines
2.5 KiB
Python
# main.py - 主业务逻辑（人脸跟踪、舵机控制、LED）
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from maix import camera, display, image, nn, app, sys
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from maix import uart, pinmap, time, err, gpio
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from maix import app, nn
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import traceback
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from config import *
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from test_face import *
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from test_ball import *
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# ------------------------------
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# 系统初始化
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# ------------------------------
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def init_system():
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"""初始化相机、舵机、串口、LED"""
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global serial_dev # 声明使用全局serial_dev
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init_led()
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# 人脸检测器
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detector = nn.YOLOv8(model="/root/models/yolov8n_face.mud", dual_buff=True)
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img_width = detector.input_width()
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img_height = detector.input_height()
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print(f"[系统] 图像尺寸: {img_width}x{img_height}")
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image_center = (img_width // 2, img_height // 2)
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# 相机/显示器
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cam = camera.Camera(img_width, img_height, detector.input_format())
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disp = display.Display()
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# 串口（舵机）
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pin_function = {"A19": "UART1_TX", "A18": "UART1_RX"}
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device = "/dev/ttyS1"
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for pin, func in pin_function.items():
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err.check_raise(pinmap.set_pin_function(pin, func),
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f"Failed set pin{pin} function to {func}")
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serial_dev = uart.UART(device, 115200)
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# 初始化值 距离中间点像素距离
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initial_cmd = f"DX:0,DY:0;"
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serial_dev.write_str(initial_cmd)
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print(f"[舵机] 初始角度: {initial_cmd}")
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time.sleep(1)
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return {
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"detector": detector, "cam": cam, "disp": disp, "serial_dev": serial_dev,
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"img_width": img_width, "img_height": img_height, "image_center": image_center
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}
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def callback(data: list[float], len: int):
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global track_mode
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# 2. 找到概率最大的关键词索引
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max_prob = max(data) # 获取最大概率值
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max_index = data.index(max_prob) # 获取最大概率对应的kw索引
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# 3. 判断：仅当最大概率>0时，输出对应value
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if max_prob > 0:
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# 根据索引映射到kw_list的value（kw0→0，kw1→1，kw2→2）
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output_value = [0, 1, 2][max_index]
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print(f"识别结果：{output_value}") # 输出最终的value
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track_mode = output_value
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# ------------------------------
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# 系统执行
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# ------------------------------
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try:
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# 初始化系统资源
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system_resources = init_system()
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# 进入主循环
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# trace_face_main(system_resources)
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trace_ball_main(system_resources)
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except Exception as e:
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print(f"[异常] 程序异常: {e}")
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traceback.print_exc()
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