Untitled1 (1).ipynb · 徐廷浪/快速傅里叶变换fft

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   "cell_type": "code",
   "execution_count": 4,
   "id": "00de5c2b-cd07-427a-a431-da1749858c43",
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   "source": [
    "\n",
    "import cv2\n",
    "import numpy as np\n",
    "\n",
    "# 读取视频文件\n",
    "cap = cv2.VideoCapture('D:/WeChat Files/wxid_vb4i1lnhest322/FileStorage/File/2023-04/bike.mp4')\n",
    "\n",
    "# 循环播放视频文件，同时显示原视频及其对应的灰度图\n",
    "while cap.isOpened():\n",
    "    # 逐帧读取视频，ret 为布尔值，表示是否成功读取帧，frame 为当前帧的图像数据\n",
    "    ret, frame = cap.read()\n",
    "    if not ret:\n",
    "        print(\"没有内容，退出啦 :) \")\n",
    "        break\n",
    "\n",
    "    # 1 使用 cv2.cvtColor() 将当前帧的彩色图像转换为灰度图\n",
    "    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    # 2 获得傅里叶系数\n",
    "    fCoef = np.fft.fft2(gray)\n",
    "\n",
    "    # print(fCoef)\n",
    "    # break          #获取一帧测试 ：成功\n",
    "\n",
    "    # 3 放大傅里叶系数，获得幅度谱(振幅谱）\n",
    "    mag_spec = 20 * np.log(np.abs(fCoef) + 1)  # 另一种常见写法: mag_spec = np.log(np.abs(fCoef))\n",
    "\n",
    "    # 4 将振幅谱转换为灰度图像\n",
    "    mag_spec = cv2.cvtColor(np.uint8(mag_spec), cv2.COLOR_GRAY2BGR)\n",
    "\n",
    "    # 5 将低频部分移至中心\n",
    "    fCoef_shifted = np.fft.fftshift(fCoef)\n",
    "\n",
    "    # 6 经过fftshift后的振幅谱\n",
    "    mag_spec_shift = 20 * np.log(np.abs(fCoef_shifted) + 1)\n",
    "\n",
    "    # 7 将fft.fftshift振幅谱转换为灰度图像\n",
    "    mag_spec_shift = cv2.cvtColor(np.uint8(mag_spec_shift), cv2.COLOR_GRAY2BGR)\n",
    "    # 8 在gray的窗口中显示灰度图像\n",
    "    cv2.imshow('mg_spc', mag_spec)\n",
    "\n",
    "    # 9 在gray窗口中显示灰度图像\n",
    "    cv2.imshow('frame', gray)\n",
    "    cv2.imshow('mag_spec_shift', mag_spec_shift)\n",
    "\n",
    "    # 每隔 1ms 检查一次用户输入，如果按下 'q' 键，退出循环\n",
    "    if cv2.waitKey(24) == ord('q'):  # 改为24ms,如果是1ms，则播放速度过快。\n",
    "        break\n",
    "\n",
    "# 释放视频捕捉资源\n",
    "cap.release()\n",
    "# 关闭所有的 GUI 窗口\n",
    "cv2.destroyAllWindows()"
   ]
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提交于 2023-04-16 14:57 . 快速傅里叶变换fft

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