Remove L6 answers

Author: cooper-mj

notebooks/lab-6/lab6-part1-numpy.ipynb

@@ -227,8 +227,8 @@
    "source": [
     "\n",
     "def crop_img(img):\n",
-    "\timg = img[250:800, 100:450, :]\n",
-    "\treturn img\n",
+    "    # Implement your function here\n",
+    "    return img\n",
     "\n",
     "img = load_image(\"cs41img.png\").copy()\n",
     "save_image(crop_img(img), \"cs41img_cropped.png\")"
@@ -261,9 +261,7 @@
    "outputs": [],
    "source": [
     "def green_img(img):\n",
-    "\timg = img[:, :, 1]\n",
-    "\tzeros = np.zeros(img.shape)\n",
-    "\timg = np.stack((zeros, img, zeros), axis=2)\n",
+    "    # Implement your function here\n",
     "\treturn img\n",
     "\n",
     "img = load_image(\"cs41img.png\").copy()\n",
@@ -296,15 +294,8 @@
    "source": [
     "\n",
     "def third_third_third(img):\n",
-    "\tred = img[:int(img.shape[0]/3), :, 0]\n",
-    "\tgreen = img[int(img.shape[0]/3):int(2*img.shape[0]/3), :, 1]\n",
-    "\tblue = img[int(2*img.shape[0]/3):, :, 2]\n",
-    "\n",
-    "\tred = np.stack((red, np.zeros(red.shape), np.zeros(red.shape)), axis=2)\n",
-    "\tgreen = np.stack((np.zeros(green.shape), np.zeros(green.shape), green), axis=2)\n",
-    "\tblue = np.stack((np.zeros(blue.shape), blue, np.zeros(blue.shape)), axis=2)\n",
-    "\n",
-    "\treturn np.concatenate((red, green, blue), axis=0)\n",
+    "    # Implement your function here\n",
+    "    return img\n",
     "\n",
     "img = load_image(\"cs41img.png\").copy()\n",
     "save_image(third_third_third(img), \"cs41img_third.png\")"
@@ -338,10 +329,7 @@
    "source": [
     "\n",
     "def brightness(img, factor):\n",
-    "\tfor row in range(img.shape[0]):\n",
-    "\t\tfor col in range(img.shape[1]):\n",
-    "\t\t\tfor color in range(img.shape[2]):\n",
-    "\t\t\t\timg[row, col, color] = min(img[row, col, color]*factor, 255)\n",
+    "    # Implement your function here\n",
     "\treturn img\n",
     "\n",
     "img = load_image(\"cs41img.png\").copy()\n",
@@ -369,14 +357,7 @@
    "outputs": [],
    "source": [
     "def contrast(img, factor):\n",
-    "\tfor row in range(img.shape[0]):\n",
-    "\t\tfor col in range(img.shape[1]):\n",
-    "\t\t\tfor color in range(img.shape[2]):\n",
-    "\t\t\t\tif img[row, col, color] < 128:\n",
-    "\t\t\t\t\timg[row, col, color] = img[row, col, color]/factor\n",
-    "\t\t\t\telse:\n",
-    "\t\t\t\t\timg[row, col, color] = min(img[row, col, color]*factor, 255)\n",
-    "\n",
+    "    # Implement your function here\n",
     "\treturn img\n",
     "\n",
     "img = load_image(\"cs41img.png\").copy()\n",
@@ -418,13 +399,7 @@
    "outputs": [],
    "source": [
     "def reconstruct(img1, img2, img3):\n",
-    "    reconstructed_img = np.zeros(img1.shape)\n",
-    "    for row in range(img1.shape[0]):\n",
-    "        for col in range(img1.shape[1]):\n",
-    "            for color in range(img1.shape[2]):\n",
-    "                pixel_choices = np.asarray([img1[row, col, color], img2[row, col, color], img3[row, col, color]])\n",
-    "                reconstructed_img[row, col, color] = np.argmax(np.bincount(pixel_choices))\n",
-    "\n",
+    "    # Implement your function here\n",
     "    return reconstructed_img\n",
     "\n",
     "img1 = load_image(\"SOLcs41img_unicorn1.png\").copy()\n",
@@ -547,7 +522,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.0"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,