ARM-benchmark.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This notebook is to create an initial benchmark for software only solutions, using demo imaging scripts/tests\n",
    "# I have made before.\n",
    "\n",
    "import cv2\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Application: Remote Sensing\n",
    "\n",
    "## NDVI - Normalized Difference Vegetation Index\n",
    "\n",
    "https://en.wikipedia.org/wiki/Normalized_difference_vegetation_index\n",
    "\n",
    "This is a common graphical indicator used for remote sensing applications, typically from satellite imagery. The algorithm, although simplified in this form can be used to determine the amount of live vegetation in the image. \n",
    "\n",
    "This example can be thought of as a simple image operation in which a mathematical expression is used to generate a result. The equation is:\n",
    "\n",
    "# NDVI = (NIR - Red)/(NIR + Red)\n",
    "\n",
    "\n",
    "This results in a value ranging from 0.0 (No vegetation, eg. soil) to 1.0 (Densest vegetation).\n",
    "\n",
    "The following cells evaluate this algorithm's speed on the ARM processor:\n",
    "1. Read both images, Near Infrared and RGB\n",
    "2. Calculate NDVI\n",
    "3. Return the calculation's time\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total calculation time: 0.46 seconds\n"
     ]
    }
   ],
   "source": [
    "start = time.time()  # timer\n",
    "\n",
    "# reading the images\n",
    "nir = mpimg.imread('images/nir.png')\n",
    "red = mpimg.imread('images/rgb.png')[:,:,0]\n",
    "\n",
    "# calculate NDVI value\n",
    "bottom = (nir.astype(float)+red.astype(float))\n",
    "bottom[bottom == 0] = 0.01  # Make sure we don't divide by zero!\n",
    "ndvi = (nir.astype(float)-red)/bottom\n",
    "\n",
    "end = time.time()\n",
    "\n",
    "result = end-start\n",
    "\n",
    "print('Total calculation time: {:.2f} seconds'.format(result))\n",
    "\n",
    "\n",
    "min = 0.\n",
    "max = 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f869c0ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization\n",
    "\n",
    "plt.figure()\n",
    "# plt.hist(ndvi.ravel(), bins=256, range=(0.0, 1.0), fc='k', ec='k')\n",
    "# plt.show()\n",
    "plt.imshow(ndvi, cmap='nipy_spectral')\n",
    "plt.clim(0.0,1.0)\n",
    "plt.axis('off')\n",
    "plt.colorbar()\n",
    "\n",
    "plt.savefig('ndvi.png') # has to come before plt.show()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Application: Video Output from USB Webcam\n",
    "\n",
    "Here we demonstrate the ability to utilize a COTS USB webcam to perform real-time processing.\n",
    "\n",
    "The following cell will showcase:\n",
    "1. Loading the overlay for HDMI output. \n",
    "2. Opening the video feed using the USB port. \n",
    "3. Displaying the video on the HDMI monitor.\n",
    "4. Recording the framerate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "require(['notebook/js/codecell'], function(codecell) {\n",
       "  codecell.CodeCell.options_default.highlight_modes[\n",
       "      'magic_text/x-csrc'] = {'reg':[/^%%microblaze/]};\n",
       "  Jupyter.notebook.events.one('kernel_ready.Kernel', function(){\n",
       "      Jupyter.notebook.get_cells().map(function(cell){\n",
       "          if (cell.cell_type == 'code'){ cell.auto_highlight(); } }) ;\n",
       "  });\n",
       "});\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pynq.overlays.base import BaseOverlay\n",
    "from pynq.lib.video import *\n",
    "base = BaseOverlay(\"base.bit\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frequency: 75600000\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<contextlib._GeneratorContextManager at 0x7f80af4748>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# monitor configuration: 640*480 @ 60Hz\n",
    "Mode = VideoMode(640,480,24)\n",
    "hdmi_out = base.video.hdmi_out\n",
    "hdmi_out.configure(Mode,PIXEL_BGR)\n",
    "hdmi_out.start()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# monitor (output) frame buffer size\n",
    "frame_out_w = 1920\n",
    "frame_out_h = 1080\n",
    "# camera (input) configuration\n",
    "frame_in_w = 640\n",
    "frame_in_h = 480"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Capture device is open: True\n"
     ]
    }
   ],
   "source": [
    "# initialize camera from OpenCV\n",
    "\n",
    "videoIn = cv2.VideoCapture(0)\n",
    "videoIn.set(cv2.CAP_PROP_FRAME_WIDTH, frame_in_w);\n",
    "videoIn.set(cv2.CAP_PROP_FRAME_HEIGHT, frame_in_h);\n",
    "\n",
    "print(\"Capture device is open: \" + str(videoIn.isOpened()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frames per second: 60.155068066463805\n",
      "Frames per second: 60.02759151308014\n",
      "Demo stopped\n",
      "Average FPS: 60.091329789771976\n"
     ]
    }
   ],
   "source": [
    "numFrames = 200 # used to calculate the FPS\n",
    "fps = 0 # placehold\n",
    "fpsData = []\n",
    "\n",
    "try:\n",
    "    while True:\n",
    "        start = time.time() # start the timer\n",
    "\n",
    "        for i in range(numFrames):\n",
    "            ret, frame_vga = videoIn.read()\n",
    "            # Display webcam image via HDMI Out\n",
    "            if (ret):      \n",
    "                outframe = hdmi_out.newframe()\n",
    "                outframe[0:480,0:640,:] = frame_vga[0:480,0:640,:]\n",
    "                cv2.putText(outframe, '{:.2f}'.format(fps), (0,30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255)) # FPS on the frame\n",
    "                hdmi_out.writeframe(outframe)\n",
    "            else:\n",
    "                raise RuntimeError(\"Failed to read from camera.\")\n",
    "\n",
    "        end = time.time()\n",
    "        fps = numFrames/(end-start)\n",
    "        fpsData.append(fps)\n",
    "        print('Frames per second: {}'.format(fps))\n",
    "except KeyboardInterrupt:\n",
    "    print('Demo stopped')\n",
    "    print('Average FPS: {}'.format(np.mean(fpsData)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Application: Video Processing\n",
    "\n",
    "Using the previous example, we then use processing methods which are the foundations for state-of-the-art techniques like neural networks. Common examples include:\n",
    "\n",
    "* Canny Edge Detection\n",
    "* Thresholding \n",
    "* Gaussian Blurring\n",
    "* Color shift"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frames per second: 20.125471347657243\n",
      "Frames per second: 20.191156048127144\n",
      "Frames per second: 20.21338905026005\n",
      "Frames per second: 20.22974238103836\n",
      "Frames per second: 20.241281364593952\n",
      "Frames per second: 20.32671887292103\n",
      "Frames per second: 20.30170778521324\n",
      "Frames per second: 20.304176047005843\n",
      "Frames per second: 20.32100401933311\n",
      "Frames per second: 20.30678156676816\n",
      "Frames per second: 20.282391276321796\n",
      "Frames per second: 20.29457025563886\n",
      "Frames per second: 20.20541745345985\n",
      "Frames per second: 20.176200894216183\n",
      "Frames per second: 20.18796550428063\n",
      "Frames per second: 20.1981689717308\n",
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      "Frames per second: 20.485267354389073\n",
      "Frames per second: 20.482183232714696\n",
      "Frames per second: 20.482787379317685\n",
      "Demo stopped\n",
      "Average FPS: 20.310998158277755\n"
     ]
    }
   ],
   "source": [
    "numFrames = 200 # used to calculate the FPS\n",
    "fps = 0 # placehold\n",
    "fpsData = []\n",
    "\n",
    "try:\n",
    "    while True:\n",
    "        start = time.time() # start the timer\n",
    "\n",
    "        for i in range(numFrames):\n",
    "            ret, frame_vga = videoIn.read()\n",
    "            # Display webcam image via HDMI Out\n",
    "            if (ret):      \n",
    "                outframe = hdmi_out.newframe()\n",
    "                laplacian_frame = cv2.Laplacian(frame_vga, cv2.CV_8U, dst=outframe)\n",
    "                cv2.putText(outframe, 'Edge Detection {:.2f}'.format(fps), (0,30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255)) # FPS on the frame\n",
    "                hdmi_out.writeframe(outframe)\n",
    "            else:\n",
    "                raise RuntimeError(\"Failed to read from camera.\")\n",
    "                readError += 1\n",
    "\n",
    "        end = time.time()\n",
    "        fps = numFrames/(end-start)\n",
    "        fpsData.append(fps)\n",
    "\n",
    "        print('Frames per second: {}'.format(fps))\n",
    "except KeyboardInterrupt:\n",
    "    print('Demo stopped')\n",
    "    print('Average FPS: {}'.format(np.mean(fpsData)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#videoIn.release()\n",
    "hdmi_out.stop()\n",
    "#del hdmi_out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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