img_capture.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "import os\n",
    "import cv2\n",
    "import time\n",
    "import uuid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "IMAGE_PATHS = 'Tensorflow/workspace/images/collectedImages'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"labels = ['hello', 'yes', 'no', 'thanks', 'iloveyou']\n",
    "number_imgs = 15\"\"\"\n",
    "\n",
    "labels = ['hello', 'yes', 'no']\n",
    "number_imgs = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "Collecting images for hello\n",
      "Collecting images for yes\n",
      "Collecting images for no\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",
    "    \n",
    "    for imgnum in range(number_imgs):\n",
    "        ref, frame = cap.read()\n",
    "        img_name = os.path.join(IMAGE_PATHS, label, label + '.' + '{}.jpg'.format(str(uuid.uuid1())))\n",
    "        cv2.imwrite(img_name, frame)\n",
    "        cv2.imshow('frame', frame)\n",
    "        time.sleep(2)\n",
    "        \n",
    "        if cv2.waitKey(1) & 0xFF == ord('q'):\n",
    "            break\n",
    "    \n",
    "    cap.release()"
   ]
  },
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