Convert image to DNA & Convert DNA to Image

DNA_encoding_decoding.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1 style=\"text-align:center\"><span style=\"color:brown\">Convert image to DNA & Convert DNA to Image</span></h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Encoding & Decoding functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def encode(kmer):\n",
    "    _map = {\"A\": 0, \"C\": 1, \"T\": 2, \"G\": 3}\n",
    "    strint = 0\n",
    "    for n in kmer:\n",
    "        curr = _map[n]\n",
    "        strint = strint | curr\n",
    "        strint = strint << 2\n",
    "\n",
    "    return strint >> 2\n",
    "\n",
    "\n",
    "def decode(kmer, kSize):\n",
    "    _map = {0: 'A', 1: 'C', 2: 'T', 3: 'G'}\n",
    "    kmer_str = \"\"\n",
    "    for i in range(kSize, 0, -1):\n",
    "        base = (kmer >> (i*2-2)) & 3\n",
    "        ch = _map[base]\n",
    "        kmer_str += ch\n",
    "\n",
    "    return kmer_str"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Images R&W Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def image_to_binary(image_path):\n",
    "    img = cv2.imread(image_path, 0)\n",
    "    ret, bw_img = cv2.threshold(img,127,255,cv2.THRESH_BINARY)\n",
    "    bw_img = np.array(bw_img)\n",
    "    bw_imAC= np.where(bw_img==255, 1, bw_img)\n",
    "    return bw_imAC"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert image binary matrix to DNA sequence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def binary_matrix_to_DNA(image_binary_matrix):\n",
    "    seq = \"\"\n",
    "    row_length = len(image_binary_matrix[0])\n",
    "    for row in image_binary_matrix:\n",
    "        row = list(map(str, row))\n",
    "        row = int(\"\".join(row), 2)\n",
    "        dna = decode(row,row_length)\n",
    "        seq += dna\n",
    "    \n",
    "    return seq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert image DNA sequence to image binary matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def DNA_to_binary_matrix(DNA_Seq, row_length):\n",
    "    binary_matrix = []\n",
    "    format_str = f'0{row_length}b'\n",
    "    for i in range(0, len(DNA_Seq), row_length):\n",
    "        seq = DNA_Seq[i:i + row_length]\n",
    "        enc = encode(seq)\n",
    "        binary = list(map(int, format(enc, format_str)))\n",
    "        binary_matrix.append(binary)\n",
    "    \n",
    "    return binary_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load image and get its binary matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View: white_diagonal.png"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"white_diagonal.png\" style=\"height:100px\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 0 0 0]\n",
      " [0 1 0 0]\n",
      " [0 0 1 0]\n",
      " [0 0 0 1]]\n"
     ]
    }
   ],
   "source": [
    "bin_array = image_to_binary(\"white_diagonal.png\")\n",
    "row_length = len(bin_array[0])\n",
    "print(bin_array)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert the binary matrix to DNA sequence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AATAAACAAAATAAAC\n"
     ]
    }
   ],
   "source": [
    "DNA = binary_matrix_to_DNA(bin_array)\n",
    "print(DNA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert the DNA back to binary matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 0 0 0]\n",
      " [0 1 0 0]\n",
      " [0 0 1 0]\n",
      " [0 0 0 1]]\n"
     ]
    }
   ],
   "source": [
    "bin_mat = np.array(DNA_to_binary_matrix(DNA, row_length)).astype(np.uint8)\n",
    "print(bin_mat)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Write it back to an image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert to grey scale\n",
    "grey = cv2.threshold(bin_mat, 0, 255, cv2.THRESH_OTSU)[1]\n",
    "\n",
    "# Write to disk\n",
    "cv2.imwrite('decoded.png', grey)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View: decoded.png"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"decoded.png\" style=\"height:100px\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ~~ Assertion ~~"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2eb8aeffa2c9129086396be6b4a5acb9  decoded.png\r\n",
      "2eb8aeffa2c9129086396be6b4a5acb9  white_diagonal.png\r\n"
     ]
    }
   ],
   "source": [
    "!md5sum decoded.png white_diagonal.png"
   ]
  }
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