Play_game.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
     ]
    }
   ],
   "source": [
    "\n",
    "import random\n",
    "from keras.models import Model ,load_model\n",
    "import cv2\n",
    "import time\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "def play_game(choice):\n",
    "    if(choice==0):\n",
    "        return \"You : Scissors\"\n",
    "    elif(choice==1):\n",
    "        return \"You : stone\"\n",
    "    elif(choice==2):\n",
    "        return \"You : paper\"\n",
    "\n",
    "def winner_game(choice):\n",
    "    choices=[0,1,2]\n",
    "    comp=random.choice(choices)\n",
    "    if(comp==0):\n",
    "        if(choice==1):\n",
    "            return \"Comp : Scissors ,You Won\"\n",
    "        elif(choice==2):\n",
    "            return \"Comp : Scissors ,You Lost\"\n",
    "        else:\n",
    "            return \"Comp : Scissors ,Draw\"\n",
    "    elif(comp==1):\n",
    "        if(choice==0):\n",
    "            return \"Comp : Stone ,You Lost\"\n",
    "        elif(choice==2):\n",
    "            return \"Comp : Stone ,You Won\"\n",
    "        else:\n",
    "            return \"Comp : Stone ,Draw\"\n",
    "    if(comp==2):\n",
    "        if(choice==1):\n",
    "            return \"Comp : Paper ,You Lost\"\n",
    "        elif(choice==0):\n",
    "            return \"Comp : Paper ,You Won\"\n",
    "        else:\n",
    "            return \"Comp : Paper ,Draw\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib,requests\n",
    "\n",
    "url=\"http://192.168.1.221:8080\"\n",
    "new_model=load_model('Stone_Paper_Scissors.h5')\n",
    "past=time.time()\n",
    "cap = cv2.VideoCapture(0)\n",
    "score_comp=0\n",
    "score_you=0\n",
    "text=\"Nothing\"\n",
    "flag=0\n",
    "while(True):\n",
    "   \n",
    "    ret, frame = cap.read()\n",
    "      \n",
    "    frame=cv2.flip(frame,1)\n",
    "    roi=frame[10:350,320:660]\n",
    "    \n",
    "    font_face = cv2.FONT_HERSHEY_SIMPLEX\n",
    "    scale = 1\n",
    "    color = (255, 0, 0)\n",
    "    thickness = cv2.FILLED\n",
    "    margin = 2\n",
    "     \n",
    "    cv2.rectangle(frame,(340,10),(620,350),(0,255,0),2)\n",
    "    hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)\n",
    "    cv2.putText(frame,\"Scores:\", (340,380), font_face, scale, (255,0,0), 2, cv2.LINE_AA)\n",
    "    cv2.putText(frame,\"You:\", (340,420), font_face, scale, (0,0,255), 2, cv2.LINE_AA)\n",
    "    cv2.putText(frame,str(score_you), (510,420), font_face, scale, (0,0,255), 2, cv2.LINE_AA)\n",
    "    cv2.putText(frame,\"Comp:\", (340,460), font_face, scale, (0,255,255), 2, cv2.LINE_AA)\n",
    "    cv2.putText(frame,str(score_comp), (510,460), font_face, scale, (0,255,255), 2, cv2.LINE_AA)\n",
    "        \n",
    "    \n",
    "    \n",
    "    cv2.imshow('original',frame)\n",
    "    k =cv2.waitKey(1)\n",
    "    \n",
    "    if (time.time()-past>10):\n",
    "        past=time.time()\n",
    "        flag=0\n",
    "    elif(time.time()-past>5):\n",
    "        cv2.putText(hsv,\"Scissor\", (30,300), font_face, scale, color, 2, cv2.LINE_AA)\n",
    "        img = cv2.resize(hsv, (320, 120))\n",
    "        img = np.array(img, dtype=\"uint8\")\n",
    "        img = img.reshape(1,120, 320, 1)\n",
    "        predictions = new_model.predict(img)\n",
    "        \n",
    "        if(time.time()-past>7):\n",
    "            \n",
    "            \n",
    "            \n",
    "            text=play_game(np.argmax(predictions))\n",
    "            if flag==0:\n",
    "                winner=winner_game(np.argmax(predictions))\n",
    "                if winner.find('Won')!=-1:\n",
    "                    score_you=score_you+1\n",
    "                elif winner.find('Lost')!=-1:\n",
    "                    score_comp=score_comp+1\n",
    "                flag=1\n",
    "            cv2.putText(hsv, text, (30,30), font_face, scale, (0,0,255), 2, cv2.LINE_AA)\n",
    "            cv2.putText(hsv, winner, (30,150), font_face, 0.6,(0,255,255), 2, cv2.LINE_AA)\n",
    "        \n",
    "    elif(time.time()-past>3):\n",
    "        cv2.putText(hsv,\"Paper\", (30,300), font_face, scale, color, 2, cv2.LINE_AA)\n",
    "    elif(time.time()-past>1):\n",
    "        cv2.putText(hsv,\"Stone\", (30,300), font_face, scale, color, 2, cv2.LINE_AA)\n",
    "        \n",
    "    \n",
    "    if k%256 == 27:\n",
    "        # ESC pressed\n",
    "        print(\"Escape hit, closing...\")\n",
    "        break\n",
    "     \n",
    "        \n",
    "    cv2.imshow('mask',hsv)\n",
    "#When everything done, release the capture\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}