MediapipeDollarPY.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mediapipe as mp # Import mediapipe\n",
    "import cv2 # Import opencv\n",
    "from dollarpy import Recognizer, Template, Point\n",
    "# import csv\n",
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import csv\n",
    "import pandas as pd\n",
    "from collections import defaultdict\n",
    "from queue import Empty\n",
    "import socket\n",
    "import pickle \n",
    "import json\n",
    "import time\n",
    "import base64\n",
    "\n",
    "mp_drawing = mp.solutions.drawing_utils # Drawing helpers\n",
    "mp_holistic = mp.solutions.holistic # Mediapipe Solutions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def poseFunction(frame):\n",
    "     with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:\n",
    "        image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n",
    "        image.flags.writeable = False        \n",
    "        results = holistic.process(image)\n",
    "        image.flags.writeable = True   \n",
    "        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)\n",
    "        mp_drawing.draw_landmarks(image, results.right_hand_landmarks, mp_holistic.HAND_CONNECTIONS, \n",
    "                                    mp_drawing.DrawingSpec(color=(80,22,10), thickness=2, circle_radius=4),\n",
    "                                    mp_drawing.DrawingSpec(color=(80,44,121), thickness=2, circle_radius=2)\n",
    "                                    )\n",
    "\n",
    "        mp_drawing.draw_landmarks(image, results.left_hand_landmarks, mp_holistic.HAND_CONNECTIONS, \n",
    "                                    mp_drawing.DrawingSpec(color=(121,22,76), thickness=2, circle_radius=4),\n",
    "                                    mp_drawing.DrawingSpec(color=(121,44,250), thickness=2, circle_radius=2)\n",
    "                                    )\n",
    "\n",
    "        mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_holistic.POSE_CONNECTIONS, \n",
    "                                    mp_drawing.DrawingSpec(color=(245,117,66), thickness=2, circle_radius=4),\n",
    "                                    mp_drawing.DrawingSpec(color=(245,66,230), thickness=2, circle_radius=2)\n",
    "                                    )\n",
    "        \n",
    "        print(results.pose_landmarks)\n",
    "        return image , results.pose_landmarks.landmark\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def CreatePoints(videoURL,label):\n",
    "    cap = cv2.VideoCapture(videoURL)\n",
    "    L_All_point = {}\n",
    "    L_selected_points = [11,12,13,14,15,16,17,18,19,20,23,24]\n",
    "    for s in L_selected_points:\n",
    "        L_All_point[s] = []\n",
    "\n",
    "    with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:\n",
    "        #List to hold Coordinates\n",
    "        points = []\n",
    "        f = {}\n",
    "    \n",
    "        while cap.isOpened():\n",
    "            ret, frame = cap.read()\n",
    "            if ret == False:\n",
    "                break\n",
    "            if ret==True:\n",
    "              \n",
    "                image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n",
    "                image.flags.writeable = False        \n",
    "\n",
    "                results = holistic.process(image)\n",
    "\n",
    "                image.flags.writeable = True   \n",
    "                image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)\n",
    "\n",
    "\n",
    "\n",
    "                mp_drawing.draw_landmarks(image, results.right_hand_landmarks, mp_holistic.HAND_CONNECTIONS, \n",
    "                                         mp_drawing.DrawingSpec(color=(80,22,10), thickness=2, circle_radius=4),\n",
    "                                         mp_drawing.DrawingSpec(color=(80,44,121), thickness=2, circle_radius=2)\n",
    "                                         )\n",
    "\n",
    "\n",
    "                mp_drawing.draw_landmarks(image, results.left_hand_landmarks, mp_holistic.HAND_CONNECTIONS, \n",
    "                                         mp_drawing.DrawingSpec(color=(121,22,76), thickness=2, circle_radius=4),\n",
    "                                         mp_drawing.DrawingSpec(color=(121,44,250), thickness=2, circle_radius=2)\n",
    "                                         )\n",
    "\n",
    "\n",
    "                mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_holistic.POSE_CONNECTIONS, \n",
    "                                         mp_drawing.DrawingSpec(color=(245,117,66), thickness=2, circle_radius=4),\n",
    "                                         mp_drawing.DrawingSpec(color=(245,66,230), thickness=2, circle_radius=2)\n",
    "                                         )\n",
    "\n",
    "                try:\n",
    "\n",
    "                    pose = results.pose_landmarks.landmark\n",
    "                    index = 0\n",
    "                    newlist=[]\n",
    "                    for s in L_All_point:\n",
    "                        p_s = Point(results.pose_landmarks.landmark[s].x , results.pose_landmarks.landmark[s].y , 1)\n",
    "                        L_All_point[s].append(p_s)\n",
    "\n",
    "                except:\n",
    "                    pass\n",
    "                        \n",
    "                \n",
    "             \n",
    "             \n",
    "                #cv2.imshow(label, image)\n",
    "\n",
    "            \n",
    "\n",
    "            if cv2.waitKey(10) & 0xFF == ord('q'):\n",
    "                break\n",
    "\n",
    "    cap.release()\n",
    "    cv2.destroyAllWindows()\n",
    "    t = []\n",
    "    for f in L_All_point:\n",
    "        t += L_All_point[f]\n",
    "    points = t\n",
    "    with open('ExercisesData.csv', 'a+' , newline = '') as f:\n",
    "        writer = csv.writer(f)\n",
    "        L = []\n",
    "        \n",
    "        class_name = label\n",
    "        L.append(class_name)\n",
    "\n",
    "        for f in L_All_point:\n",
    "            for j in L_All_point[f]:\n",
    "                pt_x = round(j.x,4)\n",
    "                pt_y = round(j.y,4)\n",
    "                point_sep = str(pt_x) + \",\" + str(pt_y)\n",
    "                L.append(point_sep)\n",
    "            L.append(',')\n",
    "        \n",
    "\n",
    "        writer.writerow(L)\n",
    "        \n",
    "    return points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#vid = \"stomach_hip_thrust.mp4\"\n",
    "\n",
    "#points = CreatePoints(vid,\"stomach,hip_thrust\")\n",
    " \n",
    "#tmpl_2 = Template('hook', points)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def GetDataFromCSV():\n",
    "    import pandas as pd\n",
    "    import csv\n",
    "    from collections import defaultdict\n",
    "    from queue import Empty\n",
    "    import csv\n",
    "    \n",
    "    my_dict = defaultdict(list)\n",
    "    with open('ExercisesData.csv', newline='') as f:\n",
    "        reader = csv.reader(f)\n",
    "        data = list(reader)\n",
    "\n",
    "    data.pop(0)\n",
    "    output = []\n",
    "    temp = []\n",
    "    outer = defaultdict(list)\n",
    "    class_name = \"\"\n",
    "    for h in data:\n",
    "        flag = 0\n",
    "        output = []\n",
    "        for item in h:\n",
    "            if flag == 0:\n",
    "                flag = 1\n",
    "                class_name = item\n",
    "                continue\n",
    "            if item == ',':\n",
    "                output.append(temp)\n",
    "                temp = []\n",
    "                continue\n",
    "            st = item.split(',')\n",
    "            pt_x = float(st[0])\n",
    "            pt_y = float(st[1])\n",
    "            f = Point(pt_x , pt_y , 1)\n",
    "            temp.append(f)\n",
    "    \n",
    "        outer[class_name].append(output)\n",
    "    \n",
    "    for o in outer:\n",
    "        print(\"before\")\n",
    "        print(outer[o][0])\n",
    "        outer[o][0] = sum(outer[o][0] , [])\n",
    "        print(\"after\")\n",
    "        print(outer[o][0])\n",
    "\n",
    "    temp_list = []\n",
    "    for t in outer:\n",
    "        tmp_curr = Template(t,outer[t][0])       \n",
    "        temp_list.append(tmp_curr)  \n",
    "    return temp_list\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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     "name": "stdout",
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      "stomach,hip_thrust\n"
     ]
    }
   ],
   "source": [
    "\n",
    "Templates = GetDataFromCSV()\n",
    "print(Templates[3].name)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "device connected\n",
      "legs\n",
      "legs\n",
      "legs\n",
      "legs\n",
      "legs\n",
      "legs\n",
      "legs\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "#testing\n",
    "\n",
    "host = '127.0.0.1'\n",
    "port = 10000\n",
    "\n",
    "    # Create a socket object\n",
    "server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n",
    "server_socket.bind((host, port))\n",
    "server_socket.listen()\n",
    "conn , addr = server_socket.accept()\n",
    "print(\"device connected\")\n",
    "id_marker = {\"1\": \"Arms\", \"2\":\"Stomach\" , \"3\":\"Thighs\" , \"4\":\"Legs\"}\n",
    "\n",
    "cap = cv2.VideoCapture('C:/Users/NoorLaptop/Desktop/HCI_Phase_1/Legs_Extension.mp4')\n",
    "#cap = cv2.VideoCapture(0)\n",
    "#cap = cv2.VideoCapture('http://192.168.8.101:4747/video')\n",
    "frame_width = int(cap.get(3))\n",
    "frame_height = int(cap.get(4))\n",
    "size = (frame_width, frame_height)\n",
    "out = cv2.VideoWriter('Experiment.avi',cv2.VideoWriter_fourcc('M','J','P','G'), 20, size)\n",
    "L2_point = []\n",
    "L_selected_points = [11,12,13,14,15,16,17,18,19,20,23,24]\n",
    "L_test_point = []\n",
    "m = {}\n",
    "#recognizer = Recognizer([Templates[0]])\n",
    "recognizer = Recognizer(Templates)\n",
    "with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:\n",
    "    \n",
    "   ct = 0\n",
    "   while(True):\n",
    "        ct += 1\n",
    "        ret, frame = cap.read()\n",
    "    \n",
    "        if frame is None:\n",
    "            break\n",
    "    \n",
    "        image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n",
    "        image.flags.writeable = False        \n",
    "        results = holistic.process(image)\n",
    "        image.flags.writeable = True   \n",
    "        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)\n",
    "        for f in L_selected_points:\n",
    "            if(results.pose_landmarks is not None):\n",
    "                p = Point(results.pose_landmarks.landmark[f].x, results.pose_landmarks.landmark[f].y , 1)\n",
    "                L_test_point.append(p)  \n",
    "\n",
    "\n",
    "        '''\n",
    "        #message = data.decode('utf-8')\n",
    "        #print(message)\n",
    "        if(ct % 5 == 0):\n",
    "         data = conn.recv(1024)\n",
    "         print(ct)\n",
    "         '''\n",
    "        with open('C:/Users/NoorLaptop/Desktop/HCI_Phase_1/TUIO_Latest/TUIO11_NET-master/bin/Debug/ID_passer.txt') as f:\n",
    "          contents = f.read()\n",
    "        \n",
    "        if(ct % 15 == 0):\n",
    "            recognizer = Recognizer(Templates)\n",
    "            result = recognizer.recognize(L_test_point)\n",
    "            res_str = result[0]\n",
    "            perc_str = str(round(result[1],3))\n",
    "            final_res = \"\"\n",
    "            true_val = id_marker[contents].lower()\n",
    "            print(true_val)\n",
    "            if(res_str is not None):\n",
    "             v = res_str.split(',')\n",
    "             k = v[0].lower()\n",
    "             fg = k == true_val\n",
    "             final_res = res_str + perc_str + str(fg) + '\\n'\n",
    "            \n",
    "           \n",
    "            conn.send(final_res.encode('utf-8'))\n",
    "            if(res_str is not None):   \n",
    "                res_info = 'the label is ' + res_str\n",
    "                res_pr = 'with ' + perc_str \n",
    "                font = cv2.FONT_HERSHEY_SIMPLEX\n",
    "                org = (50, 50)\n",
    "                fontScale = 1\n",
    "                color = (255, 0, 0)\n",
    "                thickness = 1\n",
    "                cv2.putText(frame, res_info, org, font, \n",
    "                        fontScale, color, thickness, cv2.LINE_AA)  \n",
    "                org2 = (50 , 100)\n",
    "                cv2.putText(frame, res_pr, org2, font, \n",
    "                        fontScale, color, thickness, cv2.LINE_AA)  \n",
    "                \n",
    "            L_test_point = []\n",
    "\n",
    "\n",
    "        cv2.imshow('Show',frame)       \n",
    "        #out.write(image)\n",
    "     \n",
    "   \n",
    "        \n",
    "         \n",
    "        if cv2.waitKey(10) & 0xFF == ord('q'):\n",
    "            break\n",
    "\n",
    "conn.close()\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n",
    " \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from twilio.rest import Client\n",
    "account_sid = 'ACf3af298941b9c8918711b0e060ece907'\n",
    "auth_token = 'e1e30962f7ed51792e227cf8877739bc'\n",
    "twilio_number = '+15076186720'\n",
    "my_phone_number = '+201068449753'\n",
    "with open('C:/Users/NoorLaptop/Desktop/HCI_Phase_1/TUIO_Latest/TUIO11_NET-master/bin/Debug/Messaging.txt') as f:\n",
    "    cont = f.read()\n",
    "client = Client(account_sid , auth_token)\n",
    "message = client.messages.create(body = cont , from_ = twilio_number, to=my_phone_number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "host = '127.0.0.1'\n",
    "port = 10000\n",
    "\n",
    "    # Create a socket object\n",
    "server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n",
    "server_socket.bind((host, port))\n",
    "server_socket.listen()\n",
    "conn , addr = server_socket.accept()\n",
    "print(\"device connected\")\n",
    "cap = cv2.VideoCapture('C:/Users/NoorLaptop/Desktop/HCI_Phase_1/walking.mp4')\n",
    "#cap = cv2.VideoCapture(0)\n",
    "frame_width = int(cap.get(3))\n",
    "frame_height = int(cap.get(4))\n",
    "size = (frame_width, frame_height)\n",
    "out = cv2.VideoWriter('Experiment.avi',cv2.VideoWriter_fourcc('M','J','P','G'), 20, size)\n",
    "L2_point = []\n",
    "L_selected_points = [11,12,13,14,15,16,17,18,19,20,23,24]\n",
    "L_test_point = []\n",
    "m = {}\n",
    "#recognizer = Recognizer([Templates[0]])\n",
    "recognizer = Recognizer(Templates)\n",
    "with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:\n",
    "    \n",
    "   ct = 0\n",
    "   while(True):\n",
    "        ct += 1\n",
    "        ret, frame = cap.read()\n",
    "        cv2.imshow('Show',frame)\n",
    "        '''\n",
    "        if frame is None:\n",
    "            break\n",
    "        '''\n",
    "        image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n",
    "        image.flags.writeable = False        \n",
    "        results = holistic.process(image)\n",
    "        image.flags.writeable = True   \n",
    "        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)\n",
    "        for f in L_selected_points:\n",
    "            p = Point(results.pose_landmarks.landmark[f].x, results.pose_landmarks.landmark[f].y , 1)\n",
    "            L_test_point.append(p)  \n",
    "\n",
    "\n",
    "        '''\n",
    "        #message = data.decode('utf-8')\n",
    "        #print(message)\n",
    "        if(ct % 5 == 0):\n",
    "         data = conn.recv(1024)\n",
    "         print(ct)\n",
    "         '''\n",
    "        with open('ID_passer.txt') as f:\n",
    "          contents = f.read()\n",
    "          print(contents)\n",
    "        \n",
    "        if(ct % 2 == 0):\n",
    "            recognizer = Recognizer(Templates)\n",
    "            result = recognizer.recognize(L_test_point)\n",
    "            res_str = result[0]\n",
    "            perc_str = str(result[1])\n",
    "            final_res = \"\"\n",
    "            if(res_str is not None):\n",
    "             final_res = res_str + '\\n'\n",
    "            print(res_str)\n",
    "            conn.send(final_res.encode('utf-8'))\n",
    "            if(res_str is not None):   \n",
    "                res_info = 'the label is ' + res_str\n",
    "                res_pr = 'with ' + perc_str \n",
    "                font = cv2.FONT_HERSHEY_SIMPLEX\n",
    "                org = (50, 50)\n",
    "                fontScale = 1\n",
    "                color = (255, 0, 0)\n",
    "                thickness = 1\n",
    "                cv2.putText(image, res_info, org, font, \n",
    "                        fontScale, color, thickness, cv2.LINE_AA)  \n",
    "                org2 = (50 , 100)\n",
    "                cv2.putText(image, res_pr, org2, font, \n",
    "                        fontScale, color, thickness, cv2.LINE_AA)  \n",
    "            L_test_point = []\n",
    "\n",
    "       \n",
    "        #out.write(image)\n",
    "     \n",
    "   \n",
    "        \n",
    "         \n",
    "        if cv2.waitKey(10) & 0xFF == ord('q'):\n",
    "            break\n",
    "\n",
    "conn.close()\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2\n",
    "\n",
    "cap = cv2.VideoCapture('http://192.168.8.101:4747/video')\n",
    "\n",
    "while(True):\n",
    "    ret, frame = cap.read()\n",
    "\n",
    "    cv2.imshow('frame',frame)\n",
    "    if cv2.waitKey(1) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()"
   ]
  }
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