dataCollection.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e71de8a1",
   "metadata": {},
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   "source": [
    "import cv2\n",
    "import os\n",
    "import time\n",
    "import uuid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "05eee54b",
   "metadata": {},
   "outputs": [],
   "source": [
    "IMAGES_PATH = 'Tensorflow/workspace/images/collectedimages'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "423eb8eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = ['hello','thanks','yes','no','iloveyou']\n",
    "number_imgs = 15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5a7cff7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "A subdirectory or file Tensorflow\\workspace\\images\\collectedimages\\hello already exists.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting images for hello\n",
      "Collecting images for thanks\n",
      "Collecting images for yes\n",
      "Collecting images for no\n",
      "Collecting images for iloveyou\n"
     ]
    }
   ],
   "source": [
    "for label in labels:\n",
    "    !mkdir {'Tensorflow\\workspace\\images\\collectedimages\\\\'+label} \n",
    "    cap = cv2.VideoCapture(0)\n",
    "    print('Collecting images for {}'.format(label)) \n",
    "    time.sleep(5)\n",
    "    for imgnum in range(number_imgs):\n",
    "        ret, frame = cap.read() \n",
    "        imgname = os.path.join(IMAGES_PATH, label, label+'.'+'{}.jpg'.format(str(uuid.uuid1())))\n",
    "        cv2.imwrite(imgname,frame)\n",
    "        cv2.imshow('frame',frame)\n",
    "        time.sleep(2)\n",
    "        \n",
    "        if cv2.waitKey(1) & 0xFF == ord('q'):                     \n",
    "            break \n",
    "    cap.release()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d4489300",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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