用Python替代OpenMV IDE显示openmv USB 图像

原理是利用openmv的usb模仿串口，然后用Python代码打开串口接收

能替代openmv ide 跑48帧图像

Python端需要的依赖：

需要的是：
from ultralytics import YOLO
import cv2
import numpy as np
from serial import Serial
import time
from collections import deque

pyserial              3.5

numpy                 2.0.2

ultralytics           8.3.67 

opencv-contrib-python 4.11.0.86
opencv-python         4.11.0.86

Python端代码：

from ultralytics import YOLO
import cv2
import numpy as np
from serial import Serial
import time
from collections import deque# 配置参数
SERIAL_PORT = 'COM25'  # 串口号（Windows）
BAUD_RATE = 1  # 波特率
HEADER = b'\xAA\x55\xAA\x55'  # 帧头
HEADER_LEN = len(HEADER)  # 帧头长度
FPS_WINDOW_SIZE = 30  # 计算FPS的窗口大小（帧数）# 初始化YOLO模型
model = YOLO('yolov8n.pt')  # 确认模型路径正确# 性能统计变量
fps_queue = deque(maxlen=FPS_WINDOW_SIZE)  # 存储时间戳用于计算FPS
serial_read_time = 0.0  # 串口读取耗时
inference_time = 0.0  # 推理耗时def find_header(ser):"""同步数据流，找到帧头位置"""buffer = bytearray()while True:byte = ser.read(1)if not byte:continuebuffer += byteif len(buffer) >= HEADER_LEN and buffer[-HEADER_LEN:] == HEADER:returnelif len(buffer) > 100:buffer.clear()def draw_stats(img, fps, srt, inf_t):"""在图像上绘制性能统计信息"""cv2.putText(img, f"FPS: {fps:.1f}", (10, 30),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)cv2.putText(img, f"Serial: {srt:.1f}ms", (10, 60),cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 1)cv2.putText(img, f"Inference: {inf_t:.1f}ms", (10, 90),cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 1)return imgtry:ser = Serial(SERIAL_PORT, BAUD_RATE, timeout=0.1)print(f"Connected to {SERIAL_PORT}")while True:frame_start = time.perf_counter()# 步骤1：同步到帧头find_header(ser)# 步骤2：读取图像大小size_bytes = ser.read(4)if len(size_bytes) != 4:continue# 步骤3：读取图像数据size = int.from_bytes(size_bytes, 'little')img_bytes = bytearray()read_start = time.perf_counter()while len(img_bytes) < size:remaining = size - len(img_bytes)img_bytes += ser.read(remaining)serial_read_time = (time.perf_counter() - read_start) * 1000  # ms# 解码图像decode_start = time.perf_counter()img = cv2.imdecode(np.frombuffer(img_bytes, np.uint8), cv2.IMREAD_COLOR)if img is None:continue# YOLO推理inference_start = time.perf_counter()# results = model(img, show=False, verbose=False)  # 关闭冗余输出inference_time = (time.perf_counter() - inference_start) * 1000  # ms# 计算FPSfps_queue.append(frame_start)if len(fps_queue) > 1:fps = len(fps_queue) / (fps_queue[-1] - fps_queue[0])else:fps = 0# 绘制统计信息# annotated_img = results[0].plot()annotated_img = draw_stats(img, fps, serial_read_time, inference_time)# 显示结果cv2.imshow('YOLO Detection', annotated_img)# 退出检测if cv2.waitKey(1) & 0xFF == ord('q'):breakexcept KeyboardInterrupt:print("User interrupted.")
except Exception as e:print(f"Error: {e}")
finally:ser.close()cv2.destroyAllWindows()print("Resources released.")

把openmv代码作为main放到openmv里然后断开连接重新连接，并且一定要保证openmv  ide连不到openmv

openmv端代码：

import sensor, image, time, pyb# 摄像头初始化
sensor.reset()
sensor.set_pixformat(sensor.JPEG)    # 设置JPEG压缩模式
sensor.set_framesize(sensor.QVGA)    # 分辨率320x240（可调整）
sensor.set_quality(80)               # 压缩质量（0-100，越高越清晰）
sensor.skip_frames(time=2000)        # 等待摄像头稳定usb = pyb.USB_VCP()                  # USB虚拟串口对象
HEADER = b'\xAA\x55\xAA\x55'         # 帧头标识（4字节）while True:try:img = sensor.snapshot()img_bytes = img.bytearray()  # 获取JPEG图像字节流# 发送数据包格式：[帧头(4字节) + 图像大小(4字节) + 图像数据]usb.write(HEADER)                            # 1. 发送帧头usb.write(len(img_bytes).to_bytes(4, 'little'))  # 2. 发送图像大小（小端序）usb.write(img_bytes)                         # 3. 发送图像数据time.sleep_ms(1)  # 控制帧率（约20FPS，根据实际调整）except Exception as e:print("OpenMV Error:", e)break