Image_Read_Tests_v1.ipynb

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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import ndimage as ndi\n",
    "from scipy import misc\n",
    "from skimage import feature\n",
    "from skimage.io import imread\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from PIL import Image\n",
    "from numpy import*\n",
    "\n",
    "temp=asarray(Image.open('slack_gather_1.png'))\n",
    "for j in temp:\n",
    "    new_temp = asarray([[i[0],i[1]] for i in j]) # new_temp gets the two first pixe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[255 255 255 ..., 255 255 255]\n",
      " [111 111 111 ...,  88  88 255]\n",
      " [111 111 111 ...,  88  88 255]\n",
      " ..., \n",
      " [ 56  56  56 ...,  56  56 255]\n",
      " [ 56  56  56 ...,  56  56 255]\n",
      " [ 56  56  56 ...,  56  56 255]]\n"
     ]
    }
   ],
   "source": [
    "from PIL import Image\n",
    "from numpy import*\n",
    "\n",
    "im=asarray(Image.open('slack_gather_1.png'))\n",
    "x=im.shape[0]\n",
    "y=im.shape[1]*im.shape[2]\n",
    "\n",
    "im.resize((x,y)) # a 2D array\n",
    "print(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1100, 1976)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "im.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Compute the Canny filter for two values of sigma\n",
    "edges1 = feature.canny(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "edges1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "edges2 = feature.canny(im, sigma=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "edges2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.imshow(edges2, cmap='gray');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "edges16 = feature.canny(im, sigma=1.6)\n",
    "plt.imshow(edges16, cmap='gray');\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "\n",
    "plt.savefig(\"canny_lineDetect_alpha15.png\", bbox_inches='tight', pad_inches=0, dpi=280)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
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   "source": []
  },
  {
   "cell_type": "code",
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  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
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  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.imshow(im, cmap='gray');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.imshow(edges1,cmap='gray');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.imshow(edges1, cmap='gray');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "imGray = cmap=plt.cm.gray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.imshow(edges1, cmap=plt.cm.gray)\n",
    "plt.axis('off')\n",
    "# plt.set_title('Canny filter, $\\sigma=1$', fontsize=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Compute the Canny filter for two values of sigma\n",
    "edges1 = feature.canny(im)\n",
    "edges2 = feature.canny(im, sigma=3)\n",
    "\n",
    "# display results\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(nrows=997, ncols=2396, figsize=(997, 2396),\n",
    "                                    sharex=True, sharey=True)\n",
    "\n",
    "ax1.imshow(gather_sh, cmap=plt.cm.gray)\n",
    "ax1.axis('off')\n",
    "ax1.set_title('noisy image', fontsize=20)\n",
    "\n",
    "ax2.imshow(edges1, cmap=plt.cm.gray)\n",
    "ax2.axis('off')\n",
    "ax2.set_title('Canny filter, $\\sigma=1$', fontsize=20)\n",
    "\n",
    "ax3.imshow(edges2, cmap=plt.cm.gray)\n",
    "ax3.axis('off')\n",
    "ax3.set_title('Canny filter, $\\sigma=3$', fontsize=20)\n",
    "\n",
    "fig.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
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  },
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   "cell_type": "code",
   "execution_count": null,
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  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for image_path in glob.glob('output1.png'):\n",
    "    im = misc.imread(image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from skimage.io import imread\n",
    "im = imread(\"output1.png\")\n",
    "im = np.array(im)\n",
    "im.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "indices = np.dstack(np.indices(im.shape[:2]))\n",
    "data = np.concatenate((im, indices), axis=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Compute the Canny filter for two values of sigma\n",
    "edges1 = feature.canny(im)\n",
    "edges2 = feature.canny(im, sigma=3)\n",
    "\n",
    "# display results\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(nrows=997, ncols=599, figsize=(997, 599),\n",
    "                                    sharex=True, sharey=True)\n",
    "\n",
    "ax1.imshow(gather_sh, cmap=plt.cm.gray)\n",
    "ax1.axis('off')\n",
    "ax1.set_title('noisy image', fontsize=20)\n",
    "\n",
    "ax2.imshow(edges1, cmap=plt.cm.gray)\n",
    "ax2.axis('off')\n",
    "ax2.set_title('Canny filter, $\\sigma=1$', fontsize=20)\n",
    "\n",
    "ax3.imshow(edges2, cmap=plt.cm.gray)\n",
    "ax3.axis('off')\n",
    "ax3.set_title('Canny filter, $\\sigma=3$', fontsize=20)\n",
    "\n",
    "fig.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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  {
   "cell_type": "code",
   "execution_count": null,
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "\n",
    "# Generate noisy image of a square\n",
    "# im = np.zeros((128, 128))\n",
    "# im[32:-32, 32:-32] = 1\n",
    "\n",
    "im = ndi.rotate(im, 15, mode='constant')\n",
    "im = ndi.gaussian_filter(im, 4)\n",
    "# im += 0.2 * np.random.random(im.shape, casting='unsafe')\n",
    "# numpy.multiply(A, B, out=A, casting='unsafe')\n",
    "# Compute the Canny filter for two values of sigma\n",
    "edges1 = feature.canny(im)\n",
    "edges2 = feature.canny(im, sigma=3)\n",
    "\n",
    "# display results\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(8, 3),\n",
    "                                    sharex=True, sharey=True)\n",
    "\n",
    "ax1.imshow(im, cmap=plt.cm.gray)\n",
    "ax1.axis('off')\n",
    "ax1.set_title('noisy image', fontsize=20)\n",
    "\n",
    "ax2.imshow(edges1, cmap=plt.cm.gray)\n",
    "ax2.axis('off')\n",
    "ax2.set_title('Canny filter, $\\sigma=1$', fontsize=20)\n",
    "\n",
    "ax3.imshow(edges2, cmap=plt.cm.gray)\n",
    "ax3.axis('off')\n",
    "ax3.set_title('Canny filter, $\\sigma=3$', fontsize=20)\n",
    "\n",
    "fig.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from scipy import misc\n",
    "import glob\n",
    "\n",
    "for image_path in glob.glob('output1.png'):\n",
    "    image = misc.imread(image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "png = []\n",
    "for image_path in glob.glob(\"output1.png\"):\n",
    "    png.append(misc.imread(image_path))    \n",
    "\n",
    "im = np.asarray(png)\n",
    "\n",
    "print('Importing done...', im.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Generate noisy image of a square\n",
    "# im = np.zeros((128, 128))\n",
    "# im[32:-32, 32:-32] = 1\n",
    "\n",
    "im = ndi.rotate(im, 15, mode='constant')\n",
    "im = ndi.gaussian_filter(im, 4)\n",
    "#im += 0.2 * np.random.random(im.shape)\n",
    "\n",
    "# Compute the Canny filter for two values of sigma\n",
    "edges1 = feature.canny(im)\n",
    "edges2 = feature.canny(im, sigma=3)\n",
    "\n",
    "# display results\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(8, 3),\n",
    "                                    sharex=True, sharey=True)\n",
    "\n",
    "ax1.imshow(im, cmap=plt.cm.gray)\n",
    "ax1.axis('off')\n",
    "ax1.set_title('noisy image', fontsize=20)\n",
    "\n",
    "ax2.imshow(edges1, cmap=plt.cm.gray)\n",
    "ax2.axis('off')\n",
    "ax2.set_title('Canny filter, $\\sigma=1$', fontsize=20)\n",
    "\n",
    "ax3.imshow(edges2, cmap=plt.cm.gray)\n",
    "ax3.axis('off')\n",
    "ax3.set_title('Canny filter, $\\sigma=3$', fontsize=20)\n",
    "\n",
    "fig.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# from scipy import misc\n",
    "# # f = misc.face()\n",
    "# # misc.imsave('gathers_test.png', f) # uses the Image module (PIL)\n",
    "\n",
    "# import matplotlib.pyplot as plt\n",
    "# # plt.imshow(f)\n",
    "# # plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "## Alternative\n",
    "from scipy import misc\n",
    "import glob\n",
    "\n",
    "for image_path in glob.glob('output1.png'):\n",
    "    image = misc.imread(image_path)\n",
    "    print(image.shape)\n",
    "    print(image.dtype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "png = []\n",
    "for image_path in glob.glob(\"output1.png\"):\n",
    "    png.append(misc.imread(image_path))    \n",
    "\n",
    "im = np.asarray(png)\n",
    "\n",
    "print('Importing done...', im.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gather_sh = misc.imread('gather_screenshot.png')\n",
    "type(gather_sh)      \n",
    "plt.imshow(gather_sh)\n",
    "\n",
    "gather_sh.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gather_sh.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gather_sh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Compute the Canny filter for two values of sigma\n",
    "edges1 = feature.canny(gather_sh)\n",
    "edges2 = feature.canny(gather_sh, sigma=3)\n",
    "\n",
    "# display results\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(8, 3),\n",
    "                                    sharex=True, sharey=True)\n",
    "\n",
    "ax1.imshow(gather_sh, cmap=plt.cm.gray)\n",
    "ax1.axis('off')\n",
    "ax1.set_title('noisy image', fontsize=20)\n",
    "\n",
    "ax2.imshow(edges1, cmap=plt.cm.gray)\n",
    "ax2.axis('off')\n",
    "ax2.set_title('Canny filter, $\\sigma=1$', fontsize=20)\n",
    "\n",
    "ax3.imshow(edges2, cmap=plt.cm.gray)\n",
    "ax3.axis('off')\n",
    "ax3.set_title('Canny filter, $\\sigma=3$', fontsize=20)\n",
    "\n",
    "fig.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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