AMMICO/docs/source/notebooks/Example text.ipynb

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   "source": [
    "# Text extraction on image\n",
    "Inga Ulusoy, SSC, July 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f43f327c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# if running on google colab\n",
    "# flake8-noqa-cell\n",
    "import os\n",
    "\n",
    "if \"google.colab\" in str(get_ipython()):\n",
    "    # update python version\n",
    "    # install setuptools\n",
    "    !pip install setuptools==61 -qqq\n",
    "    # install misinformation\n",
    "    !pip install git+https://github.com/ssciwr/misinformation.git -qqq\n",
    "    # mount google drive for data and API key\n",
    "    from google.colab import drive\n",
    "\n",
    "    drive.mount(\"/content/drive\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf362e60",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from IPython.display import Image, display\n",
    "import misinformation\n",
    "from misinformation import utils as mutils\n",
    "from misinformation import display as mdisplay\n",
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "27675810",
   "metadata": {},
   "outputs": [],
   "source": [
    "# download the models if they are not there yet\n",
    "!python -m spacy download en_core_web_md\n",
    "!python -m textblob.download_corpora"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6da3a7aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "images = mutils.find_files(path=\"data\", limit=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bf811ce0",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in images:\n",
    "    display(Image(filename=i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b32409f",
   "metadata": {},
   "outputs": [],
   "source": [
    "mydict = mutils.initialize_dict(images)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "7b8b929f",
   "metadata": {},
   "source": [
    "## google cloud vision API\n",
    "First 1000 images per month are free."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0891b795-c7fe-454c-a45d-45fadf788142",
   "metadata": {},
   "source": [
    "## Inspect the elements per image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c6ecc88",
   "metadata": {},
   "outputs": [],
   "source": [
    "mdisplay.explore_analysis(mydict, identify=\"text-on-image\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c3e72b5-0e57-4019-b45e-3e36a74e7f52",
   "metadata": {},
   "source": [
    "## Or directly analyze for further processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "365c78b1-7ff4-4213-86fa-6a0a2d05198f",
   "metadata": {},
   "outputs": [],
   "source": [
    "for key in mydict:\n",
    "    print(key)\n",
    "    mydict[key] = misinformation.text.TextDetector(\n",
    "        mydict[key], analyse_text=True\n",
    "    ).analyse_image()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c063eda",
   "metadata": {},
   "source": [
    "## Convert to dataframe and write csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5709c2cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "outdict = mutils.append_data_to_dict(mydict)\n",
    "df = mutils.dump_df(outdict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c4f05637",
   "metadata": {},
   "outputs": [],
   "source": [
    "# check the dataframe\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bf6c9ddb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write the csv\n",
    "df.to_csv(\"./data_out.csv\")"
   ]
  }
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