iNCLab_CLIforManualMapping.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "095e9077",
   "metadata": {},
   "source": [
    "# CLI for manual mapping\n",
    "\n",
    "* Here, **saving** means typing in the csv file.\n",
    "\n",
    "\n",
    "1. Read the csv file and put it on the df\n",
    "2. Enter the number, start frame, and end frame to reflect the correction value\n",
    "3. Save the updated df. (Save Button, Save Key = \"q\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5d1813fb",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "       Unnamed: 0  frameNum     1_X    1_Y     2_X    2_Y          3_X    3_Y  \\\n",
       "0               0        76  1127.0  810.0  1233.0  383.0  1301.000000  530.0   \n",
       "1               1        77  1127.0  810.0  1233.0  385.0  1303.000000  532.0   \n",
       "2               2        78  1127.0  810.0  1242.0  405.0  1303.000000  531.0   \n",
       "3               3        79  1127.0  810.0  1239.0  400.0  1305.000000  534.0   \n",
       "4               4        80  1127.0  810.0  1233.0  382.0  1307.000000  540.0   \n",
       "...           ...       ...     ...    ...     ...    ...          ...    ...   \n",
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       "62276       62276     62352  1380.0  539.0  1012.0  720.0  1314.216513  740.0   \n",
       "62277       62277     62353  1379.0  540.0  1003.0  719.0  1318.000000  740.0   \n",
       "\n",
       "          4_X    4_Y  ...    12_X   12_Y    13_X   13_Y    14_X   14_Y  15_X  \\\n",
       "0      1344.0  600.0  ...  1227.0  292.0  1096.0  786.0  1368.0  516.0   NaN   \n",
       "1      1344.0  600.0  ...  1232.0  308.0  1090.0  786.0  1368.0  516.0   NaN   \n",
       "2      1344.0  600.0  ...  1231.0  308.0  1087.0  786.0  1368.0  514.0   NaN   \n",
       "3      1343.0  600.0  ...  1236.0  306.0  1085.0  785.0  1368.0  514.0   NaN   \n",
       "4      1343.0  599.0  ...  1240.0  308.0  1085.0  785.0  1368.0  516.0   NaN   \n",
       "...       ...    ...  ...     ...    ...     ...    ...     ...    ...   ...   \n",
       "62273  1346.0  607.0  ...  1033.0  839.0   511.0  582.0  1404.0  514.0   NaN   \n",
       "62274  1346.0  607.0  ...  1031.0  839.0   514.0  580.0  1404.0  519.0   NaN   \n",
       "62275  1346.0  604.0  ...  1026.0  839.0   491.0  571.0  1404.0  522.0   NaN   \n",
       "62276  1346.0  604.0  ...  1024.0  839.0   525.0  577.0  1404.0  524.0   NaN   \n",
       "62277  1349.0  608.0  ...  1021.0  839.0   549.0  577.0  1407.0  533.0   NaN   \n",
       "\n",
       "       15_Y  16_X  16_Y  \n",
       "0       NaN   NaN   NaN  \n",
       "1       NaN   NaN   NaN  \n",
       "2       NaN   NaN   NaN  \n",
       "3       NaN   NaN   NaN  \n",
       "4       NaN   NaN   NaN  \n",
       "...     ...   ...   ...  \n",
       "62273   NaN   NaN   NaN  \n",
       "62274   NaN   NaN   NaN  \n",
       "62275   NaN   NaN   NaN  \n",
       "62276   NaN   NaN   NaN  \n",
       "62277   NaN   NaN   NaN  \n",
       "\n",
       "[62278 rows x 34 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "date =\"0507\" #0611 0514 0507\n",
    "#result_name = \"Result-0709-#2_enter_10min_late-Fin.csv\"\n",
    "#result_name = \"Result-0604-#10-21120_25179-Fin.csv\"\n",
    "result_name =\"Result-\"+date+\"-Maually_Fin.csv\"\n",
    "df_result_raw = \"withGrid_\"+date+\".csv\"\n",
    "\n",
    "df= pd.read_csv(df_result_raw)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e79a9999",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "if you want to quit please enter 'q' else 1~16 : 1\n",
      "enter 1 for X, 2 for Y :1\n",
      "enter 'start frame' to fix : 77\n",
      "enter 'end frame' to fix : 78\n",
      "enter value to update : 100\n",
      "XorY1\n",
      "       Unnamed: 0  frameNum     1_X    1_Y     2_X    2_Y          3_X    3_Y  \\\n",
      "0               0        76  1127.0  810.0  1233.0  383.0  1301.000000  530.0   \n",
      "1               1        77  1127.0  810.0  1233.0  385.0  1303.000000  532.0   \n",
      "2               2        78  1127.0  810.0  1242.0  405.0  1303.000000  531.0   \n",
      "3               3        79  1127.0  810.0  1239.0  400.0  1305.000000  534.0   \n",
      "4               4        80  1127.0  810.0  1233.0  382.0  1307.000000  540.0   \n",
      "...           ...       ...     ...    ...     ...    ...          ...    ...   \n",
      "62273       62273     62349  1380.0  539.0   986.0  717.0  1302.867821  740.0   \n",
      "62274       62274     62350  1380.0  539.0   991.0  718.0  1306.650718  740.0   \n",
      "62275       62275     62351  1380.0  539.0  1007.0  720.0  1310.433616  740.0   \n",
      "62276       62276     62352  1380.0  539.0  1012.0  720.0  1314.216513  740.0   \n",
      "62277       62277     62353  1379.0  540.0  1003.0  719.0  1318.000000  740.0   \n",
      "\n",
      "          4_X    4_Y  ...    12_X   12_Y    13_X   13_Y    14_X   14_Y  15_X  \\\n",
      "0      1344.0  600.0  ...  1227.0  292.0  1096.0  786.0  1368.0  516.0   NaN   \n",
      "1      1344.0  600.0  ...  1232.0  308.0  1090.0  786.0  1368.0  516.0   NaN   \n",
      "2      1344.0  600.0  ...  1231.0  308.0  1087.0  786.0  1368.0  514.0   NaN   \n",
      "3      1343.0  600.0  ...  1236.0  306.0  1085.0  785.0  1368.0  514.0   NaN   \n",
      "4      1343.0  599.0  ...  1240.0  308.0  1085.0  785.0  1368.0  516.0   NaN   \n",
      "...       ...    ...  ...     ...    ...     ...    ...     ...    ...   ...   \n",
      "62273  1346.0  607.0  ...  1033.0  839.0   511.0  582.0  1404.0  514.0   NaN   \n",
      "62274  1346.0  607.0  ...  1031.0  839.0   514.0  580.0  1404.0  519.0   NaN   \n",
      "62275  1346.0  604.0  ...  1026.0  839.0   491.0  571.0  1404.0  522.0   NaN   \n",
      "62276  1346.0  604.0  ...  1024.0  839.0   525.0  577.0  1404.0  524.0   NaN   \n",
      "62277  1349.0  608.0  ...  1021.0  839.0   549.0  577.0  1407.0  533.0   NaN   \n",
      "\n",
      "       15_Y  16_X  16_Y  \n",
      "0       NaN   NaN   NaN  \n",
      "1       NaN   NaN   NaN  \n",
      "2       NaN   NaN   NaN  \n",
      "3       NaN   NaN   NaN  \n",
      "4       NaN   NaN   NaN  \n",
      "...     ...   ...   ...  \n",
      "62273   NaN   NaN   NaN  \n",
      "62274   NaN   NaN   NaN  \n",
      "62275   NaN   NaN   NaN  \n",
      "62276   NaN   NaN   NaN  \n",
      "62277   NaN   NaN   NaN  \n",
      "\n",
      "[62278 rows x 34 columns]\n",
      "--------!!!UPDATED!!!-----------\n",
      "if you want to quit please enter 'q' else 1~16 : q\n",
      "       Unnamed: 0  frameNum     1_X    1_Y     2_X    2_Y          3_X    3_Y  \\\n",
      "0               0        76  1127.0  810.0  1233.0  383.0  1301.000000  530.0   \n",
      "1               1        77     100  810.0  1233.0  385.0  1303.000000  532.0   \n",
      "2               2        78     100  810.0  1242.0  405.0  1303.000000  531.0   \n",
      "3               3        79  1127.0  810.0  1239.0  400.0  1305.000000  534.0   \n",
      "4               4        80  1127.0  810.0  1233.0  382.0  1307.000000  540.0   \n",
      "...           ...       ...     ...    ...     ...    ...          ...    ...   \n",
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      "62277       62277     62353  1379.0  540.0  1003.0  719.0  1318.000000  740.0   \n",
      "\n",
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      "2      1344.0  600.0  ...  1231.0  308.0  1087.0  786.0  1368.0  514.0   NaN   \n",
      "3      1343.0  600.0  ...  1236.0  306.0  1085.0  785.0  1368.0  514.0   NaN   \n",
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      "...       ...    ...  ...     ...    ...     ...    ...     ...    ...   ...   \n",
      "62273  1346.0  607.0  ...  1033.0  839.0   511.0  582.0  1404.0  514.0   NaN   \n",
      "62274  1346.0  607.0  ...  1031.0  839.0   514.0  580.0  1404.0  519.0   NaN   \n",
      "62275  1346.0  604.0  ...  1026.0  839.0   491.0  571.0  1404.0  522.0   NaN   \n",
      "62276  1346.0  604.0  ...  1024.0  839.0   525.0  577.0  1404.0  524.0   NaN   \n",
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      "\n",
      "       15_Y  16_X  16_Y  \n",
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      "...     ...   ...   ...  \n",
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      "62275   NaN   NaN   NaN  \n",
      "62276   NaN   NaN   NaN  \n",
      "62277   NaN   NaN   NaN  \n",
      "\n",
      "[62278 rows x 34 columns]\n",
      "saved\n"
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       "</table>\n",
       "<p>62278 rows × 34 columns</p>\n",
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      ],
      "text/plain": [
       "       Unnamed: 0  frameNum     1_X    1_Y     2_X    2_Y          3_X    3_Y  \\\n",
       "0               0        76  1127.0  810.0  1233.0  383.0  1301.000000  530.0   \n",
       "1               1        77     100  810.0  1233.0  385.0  1303.000000  532.0   \n",
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       "4               4        80  1127.0  810.0  1233.0  382.0  1307.000000  540.0   \n",
       "...           ...       ...     ...    ...     ...    ...          ...    ...   \n",
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       "62277       62277     62353  1379.0  540.0  1003.0  719.0  1318.000000  740.0   \n",
       "\n",
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       "...       ...    ...  ...     ...    ...     ...    ...     ...    ...   ...   \n",
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       "62276  1346.0  604.0  ...  1024.0  839.0   525.0  577.0  1404.0  524.0   NaN   \n",
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       "\n",
       "       15_Y  16_X  16_Y  \n",
       "0       NaN   NaN   NaN  \n",
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       "...     ...   ...   ...  \n",
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       "\n",
       "[62278 rows x 34 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "while (1):\n",
    "    quitOrNum = input(\"if you want to quit please enter 'q' else 1~16 : \")\n",
    "    if (quitOrNum == \"q\"):\n",
    "        df.to_csv(result_name)\n",
    "        #print(df)\n",
    "        print(\"saved\")\n",
    "        break;\n",
    "\n",
    "    global_id=quitOrNum\n",
    "    XorY =input(\"enter 1 for X, 2 for Y :\")\n",
    "    start_frame =int(input(\"enter 'start frame' to fix : \")) \n",
    "    end_frame=int(input(\"enter 'end frame' to fix : \"))\n",
    "    value=input(\"enter value to update : \")\n",
    "    # df\n",
    "    if (XorY == \"1\") :\n",
    "        column =str(global_id)+\"_X\"\n",
    "        print(df)\n",
    "        for index in range(start_frame, end_frame+1):\n",
    "            df.loc[df['frameNum'] == index,column]=value\n",
    "    elif(XorY == \"2\") : \n",
    "        column =str(global_id)+\"_Y\"\n",
    "        for index in range(start_frame, end_frame+1):\n",
    "            df.loc[df['frameNum'] == index,column]=value\n",
    "    print(\"--------!!!UPDATED & NOT SAVED!!!-----------\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "291ae3ae",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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