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@prithvimk
prithvimk committed Feb 6, 2022
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1 change: 1 addition & 0 deletions .gitignore
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venv
252 changes: 252 additions & 0 deletions data_exploratory_analysis.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>hand_landmark</th>\n",
" <th>lmx</th>\n",
" <th>lmy</th>\n",
" <th>gesture</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
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"<p>25200 rows × 4 columns</p>\n",
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"text/plain": [
" hand_landmark lmx lmy gesture\n",
"0 0 245 443 two\n",
"1 1 217 412 two\n",
"2 2 202 340 two\n",
"3 3 213 278 two\n",
"4 4 235 247 two\n",
"... ... ... ... ...\n",
"25195 16 282 506 two\n",
"25196 17 327 481 two\n",
"25197 18 322 458 two\n",
"25198 19 304 489 two\n",
"25199 20 292 516 two\n",
"\n",
"[25200 rows x 4 columns]"
]
},
"execution_count": 3,
"metadata": {},
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}
],
"source": [
"df = pd.read_csv('gestures.csv')\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['HandLandmark.WRIST',\n",
" 'HandLandmark.THUMB_CMC',\n",
" 'HandLandmark.THUMB_MCP',\n",
" 'HandLandmark.THUMB_IP',\n",
" 'HandLandmark.THUMB_TIP',\n",
" 'HandLandmark.INDEX_FINGER_MCP',\n",
" 'HandLandmark.INDEX_FINGER_PIP',\n",
" 'HandLandmark.INDEX_FINGER_DIP',\n",
" 'HandLandmark.INDEX_FINGER_TIP',\n",
" 'HandLandmark.MIDDLE_FINGER_MCP',\n",
" 'HandLandmark.MIDDLE_FINGER_PIP',\n",
" 'HandLandmark.MIDDLE_FINGER_DIP',\n",
" 'HandLandmark.MIDDLE_FINGER_TIP',\n",
" 'HandLandmark.RING_FINGER_MCP',\n",
" 'HandLandmark.RING_FINGER_PIP',\n",
" 'HandLandmark.RING_FINGER_DIP',\n",
" 'HandLandmark.RING_FINGER_TIP',\n",
" 'HandLandmark.PINKY_MCP',\n",
" 'HandLandmark.PINKY_PIP',\n",
" 'HandLandmark.PINKY_DIP',\n",
" 'HandLandmark.PINKY_TIP']"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import mediapipe as mp\n",
"\n",
"mpHands = mp.solutions.hands\n",
"points = []\n",
"for point in mpHands.HandLandmark:\n",
" points.append(str(point))\n",
"\n",
"points"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[5, 6, 7], [1, 2, 3], [2, 4, 6]]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g = [[5, 6, 7]]\n",
"l = [[1, 2, 3], [2, 4, 6]]\n",
"\n",
"g += l\n",
"\n",
"g"
]
}
],
"metadata": {
"interpreter": {
"hash": "47106c6b88aeea239e5473066f6efa9ce6b28b75987194b485f6af2aeeb55b7b"
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}
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