{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/media/ppak/Storage/HuggingFace/Datasets/Melt-Pool-Thermal-Images/venv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "import pickle\n",
    "import re\n",
    "\n",
    "from datasets import Dataset, concatenate_datasets\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir = \"../../NIST-In-Situ-IN625-LPBF-Overhangs/layer/base/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def numerical_sort(value):\n",
    "    # Extract numerical part from the string\n",
    "    numbers = re.compile(r'(\\d+)')\n",
    "    parts = numbers.split(value)\n",
    "    parts[1::2] = map(int, parts[1::2])\n",
    "    return parts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 99/99 [03:09<00:00,  1.91s/it]\n"
     ]
    }
   ],
   "source": [
    "dataset = None\n",
    "layer_frames_list = []\n",
    "# for layer_file in sorted(os.listdir(data_dir), key=numerical_sort)[0:2]:\n",
    "for layer_file in tqdm(sorted(os.listdir(data_dir), key=numerical_sort)):\n",
    "    with open(f\"{data_dir}/{layer_file}\", \"rb\") as f:\n",
    "        layer = pickle.load(f)\n",
    "\n",
    "    # Transpose specific layer values\n",
    "    layer_transposed = {}\n",
    "    for key, value in layer.items():\n",
    "        if (key in [\"build_time\", \"raw_frame_number\"]):\n",
    "            # print(key, value.shape)\n",
    "            value_transposed = value.transpose(1, 0)\n",
    "            # print(key, value_transposed.shape)\n",
    "            if (key == \"raw_frame_number\"):\n",
    "                layer_transposed[key] = value_transposed.flatten()\n",
    "            else:\n",
    "                layer_transposed[key] = value_transposed\n",
    "        elif (key == \"resolution\"):\n",
    "            # print(key, value)\n",
    "            value_flatten = value.flatten()\n",
    "            # print(key, value_flatten)\n",
    "            layer_transposed[key] = value_flatten\n",
    "        else:\n",
    "            layer_transposed[key] = value\n",
    "\n",
    "    frames_list = []\n",
    "    for frame_index, frame in enumerate(layer_transposed[\"radiant_temp\"]):\n",
    "        frame_dict = {}\n",
    "        frame_dict[\"frame_index\"] = frame_index\n",
    "        for key, value in layer_transposed.items():\n",
    "            if (key in [\"radiant_temp\", \"build_time\", \"raw_frame_number\"]):\n",
    "                frame_dict[key] = value[frame_index]\n",
    "            else:\n",
    "                frame_dict[key] = value\n",
    "        \n",
    "        frames_list.append(frame_dict)\n",
    "    \n",
    "    layer_dataset = Dataset.from_list(frames_list)\n",
    "    if dataset == None:\n",
    "        dataset = layer_dataset\n",
    "    else:\n",
    "        dataset = concatenate_datasets([dataset, layer_dataset])\n",
    "\n",
    "    # layer_frames_list += frames_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "Uploading the dataset shards: 100%|██████████| 31/31 [05:00<00:00,  9.70s/it]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "CommitInfo(commit_url='https://huggingface.co/datasets/ppak10/Melt-Pool-Thermal-Images/commit/3252ef78aceb07c7bbea05c43eda0f5c7070f869', commit_message='Upload dataset', commit_description='', oid='3252ef78aceb07c7bbea05c43eda0f5c7070f869', pr_url=None, pr_revision=None, pr_num=None)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.push_to_hub(\n",
    "    \"ppak10/Melt-Pool-Thermal-Images\",\n",
    "    config_name = \"nist_overhangs_base_frame_data\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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