Skip to content

Instantly share code, notes, and snippets.

@luctrudeau
Last active March 25, 2020 15:01
Show Gist options
  • Star 1 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save luctrudeau/5fd99493504b1ebb46bf0df734dccb96 to your computer and use it in GitHub Desktop.
Save luctrudeau/5fd99493504b1ebb46bf0df734dccb96 to your computer and use it in GitHub Desktop.
Snowbird Tram CfL
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# CfL in Action\n",
"\n",
"Although The YCbCr/YUV color spaces are designed to eliminate correlation between color planes. Local correlation between color planes can exist. Chroma from Luma (CfL) exploits this correlation by predicting chroma pixels using reconstructed luma pixel values.\n",
"\n",
"In this notebook, we will demonstrate in a visual way how CfL works. To do so, we will convert an image from RGB to YCbCr and using the luma values show all possible predictions that can be acheived using barrbrain's simple 1D notebook."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"\n",
"from scipy.ndimage import imread\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import locale\n",
"\n",
"def conv_ycbcr(im):\n",
" y = np.array([0.213, 0.715, 0.072])\n",
" u = np.array([-0.115, -0.385, 0.5])\n",
" v = np.array([0.5, -0.454, -0.046])\n",
" color_matrix = np.array([y, u, v])\n",
" yuv = im.dot(color_matrix.T)\n",
" yuv[:,:,[1,2]] += 128\n",
" \n",
" return yuv\n",
"\n",
"def conv_rgb(im):\n",
" im[:,:,[1,2]] -= 128\n",
" \n",
" r = np.array([1, 0, 1.575])\n",
" g = np.array([1, -0.187, -0.468])\n",
" b = np.array([1, 1.856, 0])\n",
" color_matrix = np.array([r,g,b])\n",
" \n",
" rgb = im.dot(color_matrix.T)\n",
" rgb[rgb < 0] = 0\n",
" rgb[rgb > 255] = 255\n",
" rgb = np.uint8(rgb)\n",
" \n",
" return rgb"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In AV1, CfL is applied to intra prediction blocks. For this example, we will find a block with highly correlated luma and chroma planes."
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.377723158873948\n",
"0.5178849994095441\n",
"0.7174911969666911\n",
"0.8680479995939496\n",
"0.8768719551938995\n",
"0.9330910915829729\n",
"0.9410690003272295\n",
"0.9649898910081494\n",
"0.9911670067622436\n",
"2368\n",
"2176\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f9dee168b00>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"np.seterr(divide='ignore', invalid='ignore')\n",
"im = plt.imread(\"../images/Snowbird3.jpg\")\n",
"#im = np.round(im * 255)\n",
"yuv = conv_ycbcr(im)\n",
"height, width, planes = im.shape\n",
"block_size = 32\n",
"height = height // block_size * block_size\n",
"width = width // block_size * block_size\n",
"max_Corr = 0\n",
"for y in range(0, height, block_size):\n",
" for x in range(0, width, block_size):\n",
" block = yuv[y:y+block_size, x:x+block_size, :]\n",
" #avg = np.mean(block[:,:,0])\n",
" dy = np.ones(block_size) * round(np.mean(block[:,:,0])) - block[:,:,0]\n",
" du = np.ones(block_size) * round(np.mean(block[:,:,1])) - block[:,:,1]\n",
" dv = np.ones(block_size) * round(np.mean(block[:,:,2])) - block[:,:,2]\n",
" \n",
" corr = (np.corrcoef(dy.flatten(), du.flatten()) + np.corrcoef(dy.flatten(), dv.flatten()))/2\n",
" corr = abs(corr[0,1])\n",
" if corr > max_Corr and corr < 1:\n",
" print(corr)\n",
" max_Corr = corr\n",
" best_x = x\n",
" best_y = y\n",
"\n",
"\n",
"im = im[best_y:best_y+block_size, best_x:best_x+block_size,:]\n",
"yuv = yuv[best_y:best_y+block_size, best_x:best_x+block_size,:]\n",
"print(best_x)\n",
"print(best_y)\n",
"\n",
"\n",
"plt.figure(figsize=(10,4))\n",
"plt.subplot(1,2,1)\n",
"plt.imshow(im)\n",
"plt.title(\"Size: %d x %d\" % (block_size, block_size))\n",
"plt.axis('off');\n",
"\n",
"dy = np.ones(block_size) * round(np.mean(yuv[:,:,0])) - yuv[:,:,0]\n",
"du = np.ones(block_size) * round(np.mean(yuv[:,:,1])) - yuv[:,:,1]\n",
"dv = np.ones(block_size) * round(np.mean(yuv[:,:,2])) - yuv[:,:,2]\n",
"\n",
"plt.subplot(1,2,2)\n",
"plt.scatter(dy, du, label='Cb', color=\"b\")\n",
"plt.scatter(dy, dv, label='Cr', color=\"r\")\n",
"plt.legend(['Cb', 'Cr'])\n",
"plt.title(\"Correlation between Luma and Chroma\")\n",
"plt.xlabel(\"$\\Delta$ Luma\")\n",
"plt.ylabel(\"$\\Delta$ Chroma\");"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The prediction built by CfL is based on the reconstructed Luma pixels. In this example, we will use the original Luma pixels as the reconstructed Luma pixel\n",
"\n",
"In the AV1 version of CfL, the Chroma block is first predicted using the average pixel values of the neighboring pixels above and to the left of the block. For this example, we predict the chromatic planes using the average value of each plane."
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4xLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvAOZPmwAACfpJREFUeJzt3ctyE8kWBdCS5CeysY1Ny9jQET3o//+7vtD4cQdMbtzQOZhEFhJ7raEy6qHCWxlRh5M5e35+noA88199A8CvIfwQSvghlPBDKOGHUMIPoYQfQgk/hBJ+CHWwzYvNTmZj/51wn/8T4uxX3wA7YeTvYPDv/vnz84uuZuaHUMIPoYQfQgk/hBJ+CCX8EGqrpb5hWyyTDFHO43t2sFxt5odQwg+hhB9CCT+EEn4IJfwQaj9KfSOU36Bl5odQwg+hhB9CCT+EEn4I9fu+7Yff2QaqWWZ+CCX8EEr4IZTwQyjhh1DCD6GU+mBXdeU8pT5glPBDKOGHUMIPoYQfQgk/hFLqg1+tKtt15bwNTNtmfggl/BBK+CGU8EMo4YdQwg+hMkt9zxs+n63B+BnV36OuPuA1CD+EEn4IJfwQSvghlPBDqP0o9Y2UQjZdzoNdsoG/bzM/hBJ+CCX8EEr4IZTwQ6j9eNs/0sSg2WYzRisq1XEjx3zPa5xz5Fqdk2asmoIfX+E+XnBZ4Dcn/BBK+CGU8EMo4YdQwg+h9qPUN2JXGnv2veQ4+hy3uU5id61duY+vzdhi4FpHzdgLmfkhlPBDKOGHUMIPoYQfQgk/hNqPUt9IueY1OsQ2fb5tlgFHv1c3PWz6u3XHjN7HyPmemrHRf7MuaYfF51UJcJqmk9Ofj66ZH0IJP4QSfggl/BBK+CGU8EOo/Sj1jSwGqatvMza9JdqulD67xTE7IwtxTtO0aI47Oqpa9OqHdXLS3cjLmPkhlPBDKOGHUMIPoYQfQgk/hNqPUl9l38to2zT6rLoOt86mS62bnqa68zXddNNxPXTQpOn4uD7w4uJi7eeXl5flMTc3N/XFXsjMD6GEH0IJP4QSfggl/BBK+CHUfpf62F1VuawrHXZTUVeq7EpzA9PbwbIeOzs7K8fOz8/Lsaurqx8eu7p6Vx5zcfG2HHspMz+EEn4IJfwQSvghlPBDKG/7f8TIWoK/s003VnWVgJHtrqZpmhXHLZf1GnhdQ81yWZcCumab6+vrcqyqEpyf12/05/Ofn7fN/BBK+CGU8EMo4YdQwg+hhB9CKfX9iMSSXtc005X6Rsqi3V9jszvV6Wld6zs9fbP2864x5u7urhyr1tubpr7Ut1zWDUHPz+sfyslJve7fly//lmMvZeaHUMIPoYQfQgk/hBJ+CCX8EEqpb1d1P8tduawaG/2X7u7jsRk7Wv/xoll6btaUDt+9q9ezOz09Lcc+ffq09vNuTb2uq2+00+75uWtZXP/FHx4e6iM20FFp5odQwg+hhB9CCT+EEn4IJfwQSqnvtXU/r131pxsb0Sxy2f4VdOW85rstiupb1013cFDfSNdpd31dd9OtVn+s/fzNm/Xdft/uo3tYdZ314eFrc1yt+94VC3gCw4QfQgk/hBJ+CCX8EEr4IdR2S31dJ9KmF8fc9D5y0zR2j90x3T12C2eOdvxVmnLevFk4c7Gov0C10OVqdVsec35eL3L58ePHcqzrwjs6Wt9euFjUf/pPT/UDqRbb/J5Z04ZXnbPvEvz5wJj5IZTwQyjhh1DCD6GEH0Jt923/PrzRH7le9xRHv3P33brrVcc1vSoHB/XFlsu6Aebion7LXq251zXoXF7WW2F1b/QPDusv9+Xz57Wfj7+1r+fLviGoVt3L01Pd3dVVD17KzA+hhB9CCT+EEn4IJfwQSvgh1H6v4bfp0uGobum2riLT/fSONu8U22SdndUdOmdn5+VY12xTbYU1TXVprivZnZzU97hY1J1Oz01JrGqOmTfna7UlwnqsO2yk7KjUBwwTfggl/BBK+CGU8EMo4YdQ+13qew1dBaUa67bW6s533Iw1/zLzZuz8fLn285ubekur9+/Xb2k1TdN0fb2+O+97xx0WnXaLRT3fdGvWPT7W6+p1Za9FsRXWorlW10331JTlRjsF5/ORsp01/IBBwg+hhB9CCT+EEn4IJfwQane26+qMVDVGrzXyREbKg9/T/CyfndWLat7cvF/7+e3tqjzm9vZDOfbu3VU5dnxc1yqr0lxXDusqZV0ZsFWc9KErHY5dqTVy/93z6LYUeykzP4QSfggl/BBK+CGU8EMo4YdQv29X32j5bWTBzWLRzGma2o6/w2V9sauruptutaq76T58WF+2q/bO+3atupzXdcw9PdW1qGrBzdHOt74MWN9jeb3+hOXQaDfgSFdiVx6czwcXIP3fc/z0GYC9JPwQSvghlPBDKOGHULvT2NO9BB75iVq/hNw33fZa3X1UL2ybtfiOT+pHfHpab091f3/XjN2XY5eX69/cn52tX9tvmqZpsajvsX2TXo4MvtUfrAQ0RYfyTXpXxejuvVvDr9NdrxobrYy8lJkfQgk/hBJ+CCX8EEr4IZTwQ6jtlvpGKxdVv0R39w8D55um/uewqJYtz+pa38ePH8uxrtnm7q4r512WY1VDTVdn7daDmzV7g7Xr8RX1t+6YphrWl+bqw+pjRhuMho7q73/oPjZQBjTzQyjhh1DCD6GEH0IJP4QSfgi1O1193e5D1e5U/2mO6X7W6krZNP1bD928X3/g4WHdQrha3dbnu7kuxy4u3pZjJyfdNllVHbMuDXXrwfXba/14uakveQ1ea6BDb7RUtumSXUdXH/AqhB9CCT+EEn4IJfwQSvgh1HZLfV05r15fcpq+FJ93P1312phtx9/7+7rT7u3b9eW3v/76qzxmtVqVY2/enJZjBwd1+bArN1ULbs5mdTmv7gTsSofji2Bu+nyvXRL7VTb9fP+fmR9CCT+EEn4IJfwQSvghlPBDqO2W+rry2z/NWNXV13TgLeoqWrsA5nJZXWya/v7777Wfr1Z/lMd0HX/dWFfm+fq1W510fQno4KA+35cvVS21Lzl2q1luev+5bZYV98Em7t/MD6GEH0IJP4QSfggl/BBK+CHUdkt9X5ux7meo6gasq3LT27fn5dinT/X+edfX9aKad3d3az8/PKwfY9cV13XTzWb1Axkpe3Ulu24Bz6enbmPD3bDvZbtKv6+hUh8wSPghlPBDKOGHUMIPobb7tr97cVzvTlUed/3+ojzk9rbeJuvDhw/l2P39fTlWvYFfLOrHOJ+PvS1/fGyad5o3vY/F2/lZc77ujf58Xs8Pgzto7YRtb9e16XUGreEHDBN+CCX8EEr4IZTwQyjhh1DbLfUdN2NNBWV1v77Z5urqqjzmzz//LMe6Ut/R0VE5VpdX6rJLXyqrj3t8rPc269b+m4omna6c1zcK1ZfqbHMLrZErvXbTzGtT6gOGCT+EEn4IJfwQSvghlPBDqNk2SzLA7jDzQyjhh1DCD6GEH0IJP4QSfggl/BBK+CGU8EMo4YdQwg+hhB9CCT+EEn4IJfwQSvghlPBDKOGHUMIPoYQfQgk/hBJ+CCX8EOq/3MNvtgjlQaYAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f9dedff8320>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pred_u = yuv[:,:,1].mean()\n",
"pred_v = yuv[:,:,2].mean()\n",
"\n",
"luma = yuv[:,:,0]\n",
"u = np.ones((block_size, block_size)) * pred_u\n",
"v = np.ones((block_size, block_size)) * pred_v\n",
"\n",
"def error(im1, im2):\n",
" diff = im1 - im2\n",
" return np.round(np.sum(np.multiply(diff,diff)))\n",
"\n",
"pred_rgb = conv_rgb(np.dstack([luma, u, v]))\n",
"\n",
"plt.figure(figsize=(5,4))\n",
"plt.imshow(pred_rgb)\n",
"#plt.title(\"Prediction\\n(Luma + Average Chroma Value)\")\n",
"plt.axis('off');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next, we show all possible predictions CfL can make, using barrbrain's simple 1D code book. For each prediction, we measure the squared error and pick the best one."
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f9ded448eb8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mags = [-.5, -.25, -.125, 0, .125, .25, .5]\n",
"M = len(mags)\n",
"\n",
"ycbcr = conv_ycbcr(im)\n",
"\n",
"zm_luma = yuv[:,:,0] - yuv[:,:,0].mean()\n",
"\n",
"plt.figure(figsize=(20,15))\n",
"\n",
"min_Err = 1000000\n",
"\n",
"for x, alpha_cb in enumerate(mags):\n",
" for y, alpha_cr in enumerate(mags):\n",
" alpha_cr = -alpha_cr\n",
" u = pred_u + zm_luma * alpha_cb\n",
" v = pred_v + zm_luma * alpha_cr\n",
" \n",
" rgb = np.uint8(conv_rgb(np.dstack([luma, u, v])))\n",
" plt.subplot(M, M, y * M + x + 1)\n",
"\n",
"\n",
" \n",
" err = error(im, rgb)\n",
" if err < min_Err:\n",
" min_Err = err\n",
" best_a_cb = alpha_cb\n",
" best_a_cr = alpha_cr\n",
" \n",
" plt.imshow(np.uint8(rgb))\n",
" #plt.title(\"Squared Error: %d\" % err)\n",
" plt.axis('off')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since a correlation exists between the chromatic planes and the luma plane, we can see that CfL produces a considerably better prediction."
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f9dee07fa90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15,4))\n",
"plt.subplot(1,3,1)\n",
"plt.imshow(im)\n",
"plt.title(\"Original Block\")\n",
"plt.axis('off');\n",
"\n",
"plt.subplot(1,3,2)\n",
"plt.imshow(pred_rgb)\n",
"plt.title(\"Prediction\\n Average Chroma\\nSquared Error: %d\" % error(im, pred_rgb))\n",
"plt.axis('off');\n",
"\n",
"plt.subplot(1,3,3)\n",
"u = pred_u + zm_luma * best_a_cb\n",
"v = pred_v + zm_luma * best_a_cr\n",
"rgb = conv_rgb(np.dstack([luma, u, v]))\n",
"plt.imshow(np.uint8(rgb))\n",
"plt.title(\"CfL\\na_cb = %0.2f a_cr = %0.2f\\nSquared Error: %d\" % (best_a_cb, best_a_cr,min_Err))\n",
"plt.axis('off');"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f9dede52550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(10,4))\n",
"plt.subplot(1,2,1)\n",
"plt.imshow(im)\n",
"plt.title(\"Size: %d x %d\" % (block_size, block_size))\n",
"plt.axis('off');\n",
"\n",
"dy = np.ones(block_size) * round(np.mean(yuv[:,:,0])) - yuv[:,:,0]\n",
"du = np.ones(block_size) * round(np.mean(yuv[:,:,1])) - yuv[:,:,1]\n",
"dv = np.ones(block_size) * round(np.mean(yuv[:,:,2])) - yuv[:,:,2]\n",
"\n",
"plt.subplot(1,2,2)\n",
"plt.scatter(dy, du, color=\"b\")\n",
"plt.scatter(dy, dv, color=\"r\")\n",
"sdy = np.sort(dy.flatten())\n",
"plt.plot(sdy, sdy*best_a_cb, color=\"b\")\n",
"plt.plot(sdy, sdy*best_a_cr, color=\"r\")\n",
"plt.legend(['Pred Cb','Pred Cr', 'Cb', 'Cr'])\n",
"plt.title(\"Correlation between Luma and Chroma\")\n",
"plt.xlabel(\"$\\Delta$ Luma\")\n",
"plt.ylabel(\"$\\Delta$ Chroma\");"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f9dedef8630>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(5,4))\n",
"plt.imshow(rgb)\n",
"plt.axis('off');"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"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": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment