demo_download.ipynb

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   "source": [
    "# Download FathomNet-FGVC 2023 images\n",
    "## March 24, 2023\n",
    "\n",
    "This notebook downloads images for the [FathomNet 2023 Competition](https://www.kaggle.com/competitions/fathomnet-out-of-sample-detection/overview). It assumes that the dataset has been downloaded from Kaggle and retains the original directory structure:\n",
    "\n",
    "```\n",
    "../fathomnet-out-of-sample-detection\n",
    "    |\n",
    "    |____multilabel_classification\n",
    "    |  |____train.csv\n",
    "    |____object_detection\n",
    "    |  |____eval.json\n",
    "    |  |____train.json\n",
    "    |____category_key.csv\n",
    "    |____demo_download.ipynb\n",
    "    |____download_images.py\n",
    "    |____requirements.txt\n",
    "    |____sample_submission.csv\n",
    "```"
   ]
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   "source": [
    "### Install requirements\n",
    "This installs the requirements in the current python3 environment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install -r requirements.txt"
   ]
  },
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   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Start download\n",
    "\n",
    "First download the training data. The script `download_images.py` will by default create a new directory called `images` where all the downloaded files will live. If you want the images to live someplace else on your local machine, specify an output directory using the `--outpath` flag. This may take upwards of an hour depending on your internet connection. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!python download_images.py object_detection/train.json "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now download the evaluation data. Again, if you want to save the images to a different directory, please specify the location with the `--outpath` flag. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!python download_images.py object_detection/eval.json"
   ]
  }
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