{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Extracting CSV.ipynb","provenance":[{"file_id":"16QEImhYZs_cud_QXU91sU5yxy7_0hsQ-","timestamp":1617457751956}],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"CyQpni61v-D-","executionInfo":{"status":"ok","timestamp":1618136142351,"user_tz":-420,"elapsed":10144,"user":{"displayName":"Parinphat Wasinchaikulpat","photoUrl":"","userId":"03425585365288996198"}},"outputId":"af2ae64f-ce63-4690-e319-48e020912e40"},"source":["# install required library\n","!pip install mediapipe"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Collecting mediapipe\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/9f/42/af2507a86a81e4cce0d3adcb764a755f397238d0c7bee2d99794fdca2fc5/mediapipe-0.8.3.1-cp37-cp37m-manylinux2014_x86_64.whl (47.4MB)\n","\u001b[K     |████████████████████████████████| 47.4MB 96kB/s \n","\u001b[?25hRequirement already satisfied: protobuf>=3.11.4 in /usr/local/lib/python3.7/dist-packages (from mediapipe) (3.12.4)\n","Requirement already satisfied: wheel in /usr/local/lib/python3.7/dist-packages (from mediapipe) (0.36.2)\n","Collecting dataclasses\n","  Downloading https://files.pythonhosted.org/packages/26/2f/1095cdc2868052dd1e64520f7c0d5c8c550ad297e944e641dbf1ffbb9a5d/dataclasses-0.6-py3-none-any.whl\n","Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from mediapipe) (1.15.0)\n","Requirement already satisfied: attrs>=19.1.0 in /usr/local/lib/python3.7/dist-packages (from mediapipe) (20.3.0)\n","Requirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (from mediapipe) (4.1.2.30)\n","Requirement already satisfied: absl-py in /usr/local/lib/python3.7/dist-packages (from mediapipe) (0.12.0)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from mediapipe) (1.19.5)\n","Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from protobuf>=3.11.4->mediapipe) (54.2.0)\n","Installing collected packages: dataclasses, mediapipe\n","Successfully installed dataclasses-0.6 mediapipe-0.8.3.1\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"myUaEImsoCvA","executionInfo":{"status":"ok","timestamp":1618136160816,"user_tz":-420,"elapsed":28599,"user":{"displayName":"Parinphat Wasinchaikulpat","photoUrl":"","userId":"03425585365288996198"}},"outputId":"5d266dcc-e37f-4644-b69e-c84f4fba0fca"},"source":["# import library\n","import cv2\n","import mediapipe as mp\n","import glob\n","import csv\n","from google.colab import drive\n","# mount google drive, required passcode from chosen google account\n","drive.mount('/content/drive')"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Mounted at /content/drive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"5GOqnU8qvGW-"},"source":["# constant\n","drive_url = \"/content/drive/Shared drives/Computer Vision\"\n","dataset_url = \"/content/drive/Shared drives/Computer Vision/dataset\""],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"EeJS08mIqiYV"},"source":["# for file in glob.glob(dataset_url + \"/22_03_2021/1\" + \"/*.*\"):\n","#   print(file)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"gbSZazxmqsPp"},"source":["# function for get file name from directory\n","def getFileList(directory):\n","  file_list = []\n","  # *.* use for get every file type in directory\n","  for file in glob.glob(dataset_url + directory + \"/*.*\"):\n","    # print(file)\n","    file_list.append(file)\n","  return file_list\n","\n","# function call mediapipe for static image\n","# input is directory from dataset folder onward, eg. /22_03_2021/1\n","# output store in output_dataset with the same folder\n","def extractCSV(directory):\n","  file_list = getFileList(directory)\n","  mp_drawing = mp.solutions.drawing_utils\n","  mp_hands = mp.solutions.hands\n","  row_list = [['number']]\n","  for i in range(21):\n","    row_list[0].append(str(i) + 'x')\n","    row_list[0].append(str(i) + 'y')\n","    row_list[0].append(str(i) + 'z')\n","  with mp_hands.Hands(\n","      static_image_mode=True,\n","      max_num_hands=2,\n","      min_detection_confidence=0.5) as hands:\n","    for idx, file in enumerate(file_list):\n","      # Read an image, flip it around y-axis for correct handedness output (see\n","      # above).\n","      image = cv2.flip(cv2.imread(file), 1)\n","      # Convert the BGR image to RGB before processing.\n","      results = hands.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))\n","\n","      # Print handedness and draw hand landmarks on the image.\n","      # print('Handedness:', results.multi_handedness)\n","      if not results.multi_hand_landmarks:\n","        continue\n","      image_height, image_width, _ = image.shape\n","      annotated_image = image.copy()\n","      for hand_landmark in results.multi_hand_landmarks:\n","        row = [idx]\n","        for i in range(21):\n","          row.append(hand_landmark.landmark[i].x)\n","          row.append(hand_landmark.landmark[i].y)\n","          row.append(hand_landmark.landmark[i].z)\n","      maxx = 0\n","      minx = 1000\n","      maxy = 0\n","      miny = 1000\n","      maxz = 0\n","      minz = 1000\n","      for i in range(1,len(row),3):\n","        if row[i] > maxx:\n","          maxx = row[i]\n","        if row[i] < minx:\n","          minx = row[i]\n","      for i in range(1,len(row),3):\n","        row[i] = (row[i]-minx)/(maxx-minx)\n","      for i in range(2,len(row),3):\n","        if row[i] > maxy:\n","          maxy = row[i]\n","        if row[i] < miny:\n","          miny = row[i]\n","      for i in range(2,len(row),3):\n","        row[i] = (row[i]-miny)/(maxy-miny)\n","      for i in range(3,len(row),3):\n","        if row[i] > maxz:\n","          maxz = row[i]\n","        if row[i] < minz:\n","          minz = row[i]\n","      for i in range(3,len(row),3):\n","        row[i] = (row[i]-minz)/(maxz-minz)\n","      row_list.append(row)\n","    print(row_list)\n","        \n","        # print(\n","        #     f'Index finger tip coordinates: (',\n","        #     f'{hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP].x * image_width}, '\n","        #     f'{hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP].y * image_height})'\n","        # )\n","    save_dir = drive_url + \"/CSV\" + \"/\" + directory[-1] + '.csv'\n","    if directory[-2] != \"/\":\n","      print('yes')\n","      save_dir = drive_url + \"/CSV\" + \"/\" + directory[-2::] + '.csv'\n","    print(save_dir)\n","      # cv2.imwrite(save_dir, cv2.flip(annotated_image, 1))\n","    with open(save_dir, 'w', newline='') as file:\n","      writer = csv.writer(file)\n","      writer.writerows(row_list)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"UhGh_m6x0-Sb","executionInfo":{"status":"ok","timestamp":1618136422206,"user_tz":-420,"elapsed":289974,"user":{"displayName":"Parinphat Wasinchaikulpat","photoUrl":"","userId":"03425585365288996198"}},"outputId":"7e58358a-c15d-4327-f6f0-00fbe94b7449"},"source":["# getFileList(\"/22_03_2021/1\")\n","name_list = [\"1\",\"2\",\"3\",\"4\",\"5\",\"ก\",\"ง2\",\"จ1\",\"จ2\",\"ฉ1\",\"ซ2\",\"ด\",\"ต\",\"ท1\",\"น\",\"บ\",\"พ\",\"ฟ\",\"ม\",\"ย\",\"ร\",\"ล\",\"ว\",\"ส\",\"ห\",\"อ\"]\n","name_list2 = [\"5\",\"จ2\",\"ฉ1\"]\n","name_list3 = [\"ท1\",\"น\",\"บ\",\"พ\",\"ฟ\",\"ม\",\"ย\",\"ร\",\"ล\",\"ว\",\"ส\",\"ห\",\"อ\"]\n","for name in name_list3:\n","  extractCSV(\"/09_04_2021/\" + name)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[['number', '0x', '0y', '0z', '1x', '1y', '1z', '2x', '2y', '2z', '3x', '3y', '3z', '4x', '4y', '4z', '5x', '5y', '5z', '6x', '6y', '6z', '7x', '7y', '7z', '8x', '8y', '8z', '9x', '9y', '9z', '10x', '10y', '10z', '11x', '11y', '11z', '12x', '12y', '12z', '13x', '13y', '13z', '14x', '14y', '14z', '15x', '15y', '15z', '16x', '16y', '16z', '17x', '17y', '17z', '18x', '18y', '18z', '19x', '19y', '19z', '20x', '20y', '20z'], [0, 0.5513658385273358, 1.0, 0.9992040187208905, 0.22711994519239567, 0.9010821541628781, 0.7788794936432812, 0.0, 0.5820972158985197, 0.6399547487817479, 0.07531760962078761, 0.32768180558812765, 0.5019773458330197, 0.26039280270824544, 0.1399517121923887, 0.36514150416814867, 0.1273317221325871, 0.2735582564010604, 0.7012241713678953, 0.0034772479263043025, 0.0, 0.2749332654867946, 0.03000850231972739, 0.1952136624644373, 0.05995145164765839, 0.08631617471485986, 0.40644410045895946, 0.0, 0.4322092864969327, 0.26363992348551774, 0.6504238764431453, 0.366620026645065, 0.19709524631386105, 0.16337548645708663, 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