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-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Clean Human Pose MPI Dataset\n",
- "\n",
- "Fix data\n",
- "\n",
- "Data structure:\n",
- "- `data[2]` = 2 x 7 x 100 array\n",
- "- `data[2][0]` = x locations\n",
- "- `data[2][0]` = y locations\n",
- "- ordering is `0 Head, 1 Right wrist, 2 Left wrist, 3 Right elbow, 4 Left elbow, 5 Right shoulder and 6 Left shoulder`"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 175,
- "metadata": {},
- "outputs": [],
- "source": [
- "%reload_ext autoreload\n",
- "%autoreload 2\n",
- "\n",
- "import os\n",
- "from os.path import join\n",
- "import math\n",
- "from glob import glob\n",
- "from random import randint\n",
- "\n",
- "import cv2 as cv\n",
- "import numpy as np\n",
- "import pandas as pd\n",
- "from PIL import Image, ImageDraw\n",
- "%matplotlib inline\n",
- "import matplotlib.pyplot as plt\n",
- "import scipy.io\n",
- "from pathlib import Path\n",
- "from sklearn import preprocessing\n",
- "\n",
- "import sys\n",
- "sys.path.append('/work/megapixels_dev/megapixels/')\n",
- "from app.settings import app_cfg as cfg\n",
- "from app.utils import file_utils"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 176,
- "metadata": {},
- "outputs": [],
- "source": [
- "DATA_STORE = '/data_store_nas/'\n",
- "fp_dataset = join(DATA_STORE, 'datasets/people/youtube_poses')\n",
- "dir_fp_frames = join(fp_dataset, 'YouTube_Pose_dataset_1.0/GT_frames')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 177,
- "metadata": {},
- "outputs": [],
- "source": [
- "dirs_frames = glob(join(dir_fp_frames, '*'))\n",
- "fps_frames = {}\n",
- "for dir_frames in dirs_frames:\n",
- " fps_frames[dir_frames] = join(dir_frames, '*')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 178,
- "metadata": {},
- "outputs": [],
- "source": [
- "fp_pose_data = join(fp_dataset, 'YouTube_Pose_dataset_1.0/YouTube_Pose_dataset.mat')\n",
- "fp_out = join(fp_dataset, 'poses.csv')\n",
- "pose_data = scipy.io.loadmat(fp_pose_data)['data'][0]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 182,
- "metadata": {},
- "outputs": [],
- "source": [
- "# convert data to pandas DF for sanity\n",
- "poses = []\n",
- "for i, pose in enumerate(pose_data):\n",
- "\n",
- " video_id = pose[1][0]\n",
- " pose_pts = pose[2]\n",
- " crop_x1 = int(pose[6][0][0])\n",
- " crop_y1 = int(pose[6][0][1])\n",
- " crop_x2 = int(pose[6][0][2])\n",
- " crop_y2 = int(pose[6][0][3])\n",
- " w = pose[7][0][0]\n",
- " h = pose[7][0][1]\n",
- " scale = pose[5][0][0]\n",
- " \n",
- " for j in range(pose_pts.shape[2]): # 100 frames\n",
- " x = [pose_pts[0][i][j] for i in range(7)]\n",
- " y = [pose_pts[1][i][j] for i in range(7)]\n",
- " poses.append({\n",
- " 'video_id': video_id, \n",
- " 'scale': scale,\n",
- " 'crop_x1': crop_x1,\n",
- " 'crop_y1': crop_y1,\n",
- " 'crop_x2': crop_x2,\n",
- " 'crop_y2': crop_y2,\n",
- " 'width': w, \n",
- " 'height': h,\n",
- " 'head_x': x[0],\n",
- " 'head_y': y[0],\n",
- " 'wrist_right_x': x[1],\n",
- " 'wrist_right_y': y[1],\n",
- " 'wrist_left_x': x[2], \n",
- " 'wrist_left_y': y[2],\n",
- " 'elbow_right_x': x[3],\n",
- " 'elbow_right_y': y[3],\n",
- " 'elbow_left_x': x[4], \n",
- " 'elbow_left_y': y[4],\n",
- " 'shoulder_right_x': x[5],\n",
- " 'shoulder_right_y': y[5],\n",
- " 'shoulder_left_x': x[6], \n",
- " 'shoulder_left_y': y[6],\n",
- " })\n",
- "df_poses = pd.DataFrame.from_dict(poses)\n",
- "df_poses.to_csv(fp_out)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 183,
- "metadata": {},
- "outputs": [
- {
- "data": {
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- "execution_count": 183,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df_poses.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 172,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "22"
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- "execution_count": 172,
- "metadata": {},
- "output_type": "execute_result"
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- "len(df_poses.keys())"
- ]
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- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
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- "name": "megapixels"
- },
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- "pygments_lexer": "ipython3",
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- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
generated by cgit v1.2.3-70-g09d2 (git 2.51.0) at 2025-12-10 07:41:17 +0000