泰山派调试常用命令

ubuntu下使用命令行连接wifi

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sudo iwlist scan
nmcli device wifi list
nmcli device wifi connect {ESSID} password {PASSWORD}
nmcli device wifi connect 404_2.4g password "@404@404" 
nmcli device wifi connect "404_5g" password "@404@404@404" ifname wlan0
make modules_install INSTALL_MOD_PATH=<rootfs_path>

image-20250305184418243

image-20250305184435807
image-20250305184435807
image-20250305184444185
image-20250305184444185

备忘录

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 v4l2-ctl --list-devices
v4l2-ctl --list-formats-ext --device=/dev/video0
v4l2-ctl -d /dev/video0 -L
v4l2-ctl --set-ctrl analogue_gain=80


v4l2-ctl --verbose -d /dev/video0 --set-fmt-video=width=1920,height=1080,pixelformat='UYVY' --stream-mmap=20 --set-selection=target=crop,flags=0,top=0,left=0,width=1920,height=1080 --set-ctrl analogue_gain=80  --stream-to=/tmp/out.yuv

v4l2-ctl --verbose -d /dev/video1 --set-fmt-video=width=1920,height=1080,pixelformat='UYVY' --stream-mmap=20 --stream-to=/tmp/out.yuv

ffmpeg -f v4l2 -input_format nv12 -video_size 1920x1080 -i /dev/video0 -c:v libx264 -preset ultrafast output.mp4

ffmpeg -f v4l2 -i /dev/video0 -pixel_format yuv422p -framerate 15 -video_size 800x600 -c:v copy -f mpegts udp://@:1234

ffmpeg -f v4l2 -input_format nv12 -video_size 1920x1080 -i /dev/video8 -t 10 output.yuv

ffmpeg -f rawvideo -pixel_format yuv422p -video_size 3840x2160 -framerate 24 -i out.yuv -c:v libx264 output.mp4


scp lsc@192.168.115.129:/home/lsc/project/Release/kernel/boot.img ./

硬件编码测试

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# -*- coding: utf-8 -*-
import cv2
import socket
import numpy as np
import time

# --- 配置 ---
TARGET_IP = "192.168.3.71"  # 接收端电脑的 IP 地址 (运行 OBS 的电脑)
TARGET_PORT = 1234          # 目标 UDP 端口 (与 OBS 设置一致)
CAMERA_INDEX = 0            # 摄像头的索引 (通常是 0 或 1)
JPEG_QUALITY = 70           # JPEG 编码质量 (0-100, 越高画质越好但数据量越大)
SEND_RESOLUTION = (640, 480) # 发送的分辨率 (宽, 高)

# --- 初始化 ---
# 创建 UDP socket
udp_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)

# 打开摄像头
cap = cv2.VideoCapture(CAMERA_INDEX)

if not cap.isOpened():
    print(f"错误：无法打开摄像头索引 {CAMERA_INDEX}")
    exit()

# 设置摄像头分辨率 (可选, 尝试设置)
# cap.set(cv2.CAP_PROP_FRAME_WIDTH, SEND_RESOLUTION[0])
# cap.set(cv2.CAP_PROP_FRAME_HEIGHT, SEND_RESOLUTION[1])

print(f"摄像头已打开。将推流到 UDP {TARGET_IP}:{TARGET_PORT}")
print(f"发送分辨率: {SEND_RESOLUTION}, JPEG 质量: {JPEG_QUALITY}")
print("按 Ctrl+C 停止推流。")

try:
    while True:
        # 读取一帧
        ret, frame = cap.read()
        if not ret:
            print("错误：无法读取摄像头帧。")
            time.sleep(0.5) # 等待一下再试
            continue

        # 调整帧大小
        frame_resized = cv2.resize(frame, SEND_RESOLUTION)

        # 将帧编码为 JPEG
        encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), JPEG_QUALITY]
        result, encoded_frame = cv2.imencode('.jpg', frame_resized, encode_param)

        if not result:
            print("错误：JPEG 编码失败。")
            continue

        # 将编码后的数据转换为字节
        data = encoded_frame.tobytes()

        # 发送数据
        # UDP 对于数据包大小有限制 (通常 < 65507 字节)
        # 如果编码后的帧太大，可能会发送失败或被截断
        if len(data) > 65000:
            print(f"警告：帧数据过大 ({len(data)} 字节)，可能无法完整发送。尝试降低分辨率或 JPEG 质量。")
            # 可以选择跳过此帧或尝试发送
            # continue # 选择跳过

        try:
            udp_socket.sendto(data, (TARGET_IP, TARGET_PORT))
            # print(f"Sent frame: {len(data)} bytes") # 取消注释以查看发送日志
        except socket.error as e:
            print(f"发送错误: {e}")
            time.sleep(1) # 发送失败时稍作等待

        # (可选) 稍微降低帧率，减轻 CPU 负担和网络拥堵
        # time.sleep(0.01) # 约等于 100 FPS 的延迟，根据需要调整

except KeyboardInterrupt:
    print("\n停止推流...")

finally:
    # 清理资源
    print("正在释放资源...")
    cap.release()
    udp_socket.close()
    cv2.destroyAllWindows() # 如果在开发板上有显示窗口的话
    print("资源已释放。")
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-> Device Drivers                                                                                                                                                                                    │
  │       -> Multimedia support (MEDIA_SUPPORT [=y])                                                                                                                                                         │
  │         -> Media drivers                                                                                                                                                                                 │
  │ (1)       -> V4L platform devices (V4L_PLATFORM_DRIVERS [=y])

pip install opencv-python numpy

sudo apt install -y libgl1