vdma_test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# VDMA Test\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "モジュールのロード"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pynq.drivers.xlnk\n",
    "from pynq.mmio import MMIO\n",
    "\n",
    "import numpy as np\n",
    "import cv2\n",
    "from IPython.display import Image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "連続した物理メモリを確保するためのアロケータを準備"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<pynq.drivers.xlnk.xlnk object at 0x2bc27d10>\n"
     ]
    }
   ],
   "source": [
    "mmu = pynq.drivers.xlnk.xlnk()\n",
    "print(mmu)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1280x720x3 をアロケート\n",
    "確保したメモリの仮想アドレス、物理アドレスを表示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "buf = mmu.cma_alloc(1280*720*3)\n",
    "buf_phy = pynq.drivers.xlnk.libxlnk.cma_get_phy_addr(buf)\n",
    "print(\"virtal\", buf, \"physical\", hex(buf_phy))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "VDMA IPのレジスタに対するMMIOを得る"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<pynq.mmio.MMIO object at 0x2bc27bb0>\n"
     ]
    }
   ],
   "source": [
    "m = MMIO(0x43000000, 0xFF)\n",
    "print(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "VDMA IPのレジスタ設定"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "m.write(0x30, 0x8b)     # Init VDMA\n",
    "m.write(0xAC, buf_phy)  # buf LSB\n",
    "m.write(0xA8, 1280 * 3) # stride\n",
    "m.write(0xA4, 1280 * 3) # bytes per line"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "画像の縦の長さを書き込んだ瞬間に DMA がはじまる"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "m.write(0xA0, 720)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "バッファの先頭を表示。何も書き込まれていなければ多分 00,00,00, ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'\\x19\\x19\\x1b\\x17\\x18\\x19\\x19\\x1a\\x1c\\x18\\x19\\x19\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x14\\x18\\x19\\x1a\\x19\\x19\\x1c\\x19\\x19\\x1d\\x18\\x19\\x19\\x18\\x19\\x19\\x18\\x19\\x19\\x18\\x19\\x19\\x19\\x19\\x19\\x19'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mmu.cma_get_buffer(buf,64)[:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "画像を uint8 のアレイと見なして目的解像度・震度で reshape し OpenCV で扱えるフォーマットに変換\n",
    "表示してみる"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "img = np.frombuffer(mmu.cma_get_buffer(buf,1280*720*3), dtype=np.uint8).reshape((720, 1280, 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cv2.imwrite('/tmp/png.png', img)\n",
    "Image(filename='/tmp/png.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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