starnet_v1_TF2_transform.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "import tensorflow as tf\n",
    "from PIL import Image as img\n",
    "import logging\n",
    "tf.get_logger().setLevel(logging.ERROR)\n",
    "from starnet_v1_TF2 import StarNet\n",
    "\n",
    "import tifffile as tiff\n",
    "\n",
    "%reload_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Load a model. There are two modes - RGB and Greyscale.</h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "starnet = StarNet(mode = 'Greyscale', window_size = 512, stride = 128)\n",
    "starnet.load_model('./weights', './history')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Load and transform an image.</h3>\n",
    "\n",
    "<b>Now can work with either 8bit or 16bit TIFF files!</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_name = \"rgb_test5_L16.tif\"\n",
    "out_name = \"rgb_test5_L16_starless.tif\"\n",
    "starnet.transform(in_name, out_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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