Lecture 3.2 - Translations.ipynb

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    "## Translations\n",
    "\n",
    "This an affine transform that simply shifts the position of an image.\n",
    "\n",
    "We use cv2.warpAffine to implement these transformations.\n"
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    "import cv2\n",
    "import numpy as np\n",
    "\n",
    "image = cv2.imread('images/input.jpg')\n",
    "\n",
    "# Store height and width of the image\n",
    "height, width = image.shape[:2]\n",
    "\n",
    "quarter_height, quarter_width = height/4, width/4\n",
    "\n",
    "#       | 1 0 Tx |\n",
    "#  T  = | 0 1 Ty |\n",
    "#       | Stauchung/Dehnung entlang der X-Achse, Drehen um die Kante (0,0) gegen den Uhrzeigersinn, Bewegen entlang der x-Achse |\n",
    "#  T  = | Stauchung/Dehnung entlang der y-Achse ,Drehen um die Kante (0,0) mit den Uhrzeigersinn, Bewegen entlang der y-Achse |\n",
    "\n",
    "# T is our translation matrix\n",
    "T = np.float32([[1, 0, -50], [0, 1,-50]])\n",
    "\n",
    "# We use warpAffine to transform the image using the matrix, T\n",
    "# cv2.warpAffine(Source, Transformation, (Destination)\n",
    "img_translation = cv2.warpAffine(image, T, (width/2, height/2))\n",
    "cv2.imshow('Translation', img_translation)\n",
    "cv2.waitKey()\n",
    "cv2.destroyAllWindows()"
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      "[[   1.    0.  311.]\n",
      " [   0.    1.  207.]]\n"
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    "# Let's take a look at T\n",
    "\n",
    "print T"
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