fix problems in net_surgery.ipynb

examples/net_surgery.ipynb

@@ -22,7 +22,6 @@
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "%matplotlib inline\n",
-    "import Image\n",
     "\n",
     "# Make sure that caffe is on the python path:\n",
     "caffe_root = '../'  # this file is expected to be in {caffe_root}/examples\n",
@@ -3511,7 +3510,7 @@
     "print(\"blobs {}\\nparams {}\".format(net.blobs.keys(), net.params.keys()))\n",
     "\n",
     "# load image and prepare as a single input batch for Caffe\n",
-    "im = np.array(Image.open('images/cat_gray.jpg'))\n",
+    "im = np.array(caffe.io.load_image('images/cat_gray.jpg', color=False)).squeeze()\n",
     "plt.title(\"original image\")\n",
     "plt.imshow(im)\n",
     "plt.axis('off')\n",
@@ -4480,8 +4479,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "pre-surgery output mean -12.93\n",
-      "post-surgery output mean -11.93\n"
+      "pre-surgery output mean -0.02\n",
+      "post-surgery output mean 0.98\n"
      ]
     }
    ],
@@ -4489,7 +4488,7 @@
     "# pick first filter output\n",
     "conv0 = net.blobs['conv'].data[0, 0]\n",
     "print(\"pre-surgery output mean {:.2f}\".format(conv0.mean()))\n",
-    "# set first filter bias to 10\n",
+    "# set first filter bias to 1\n",
     "net.params['conv'][1].data[0] = 1.\n",
     "net.forward()\n",
     "print(\"post-surgery output mean {:.2f}\".format(conv0.mean()))"
@@ -5494,13 +5493,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1,2c1,2\r\n",
+      "1,2c1\r\n",
       "< # Fully convolutional network version of CaffeNet.\r\n",
       "< name: \"CaffeNetConv\"\r\n",
       "---\r\n",
       "> name: \"CaffeNet\"\r\n",
-      "> input: \"data\"\r\n",
-      "7,11c7\r\n",
+      "7,11c6\r\n",
       "<   input_param {\r\n",
       "<     # initial shape for a fully convolutional network:\r\n",
       "<     # the shape can be set for each input by reshape.\r\n",
@@ -5508,33 +5506,33 @@
       "<   }\r\n",
       "---\r\n",
       ">   input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }\r\n",
-      "157,158c153,154\r\n",
+      "157,158c152,153\r\n",
       "<   name: \"fc6-conv\"\r\n",
       "<   type: \"Convolution\"\r\n",
       "---\r\n",
       ">   name: \"fc6\"\r\n",
       ">   type: \"InnerProduct\"\r\n",
-      "160,161c156,157\r\n",
+      "160,161c155,156\r\n",
       "<   top: \"fc6-conv\"\r\n",
       "<   convolution_param {\r\n",
       "---\r\n",
       ">   top: \"fc6\"\r\n",
       ">   inner_product_param {\r\n",
-      "163d158\r\n",
+      "163d157\r\n",
       "<     kernel_size: 6\r\n",
-      "169,170c164,165\r\n",
+      "169,170c163,164\r\n",
       "<   bottom: \"fc6-conv\"\r\n",
       "<   top: \"fc6-conv\"\r\n",
       "---\r\n",
       ">   bottom: \"fc6\"\r\n",
       ">   top: \"fc6\"\r\n",
-      "175,176c170,171\r\n",
+      "175,176c169,170\r\n",
       "<   bottom: \"fc6-conv\"\r\n",
       "<   top: \"fc6-conv\"\r\n",
       "---\r\n",
       ">   bottom: \"fc6\"\r\n",
       ">   top: \"fc6\"\r\n",
-      "182,186c177,181\r\n",
+      "182,186c176,180\r\n",
       "<   name: \"fc7-conv\"\r\n",
       "<   type: \"Convolution\"\r\n",
       "<   bottom: \"fc6-conv\"\r\n",
@@ -5546,21 +5544,21 @@
       ">   bottom: \"fc6\"\r\n",
       ">   top: \"fc7\"\r\n",
       ">   inner_product_param {\r\n",
-      "188d182\r\n",
+      "188d181\r\n",
       "<     kernel_size: 1\r\n",
-      "194,195c188,189\r\n",
+      "194,195c187,188\r\n",
       "<   bottom: \"fc7-conv\"\r\n",
       "<   top: \"fc7-conv\"\r\n",
       "---\r\n",
       ">   bottom: \"fc7\"\r\n",
       ">   top: \"fc7\"\r\n",
-      "200,201c194,195\r\n",
+      "200,201c193,194\r\n",
       "<   bottom: \"fc7-conv\"\r\n",
       "<   top: \"fc7-conv\"\r\n",
       "---\r\n",
       ">   bottom: \"fc7\"\r\n",
       ">   top: \"fc7\"\r\n",
-      "207,211c201,205\r\n",
+      "207,211c200,204\r\n",
       "<   name: \"fc8-conv\"\r\n",
       "<   type: \"Convolution\"\r\n",
       "<   bottom: \"fc7-conv\"\r\n",
@@ -5572,9 +5570,9 @@
       ">   bottom: \"fc7\"\r\n",
       ">   top: \"fc8\"\r\n",
       ">   inner_product_param {\r\n",
-      "213d206\r\n",
+      "213d205\r\n",
       "<     kernel_size: 1\r\n",
-      "219c212\r\n",
+      "219c211\r\n",
       "<   bottom: \"fc8-conv\"\r\n",
       "---\r\n",
       ">   bottom: \"fc8\"\r\n"
@@ -5610,13 +5608,6 @@
     }
    ],
    "source": [
-    "# Make sure that caffe is on the python path:\n",
-    "caffe_root = '../'  # this file is expected to be in {caffe_root}/examples\n",
-    "import sys\n",
-    "sys.path.insert(0, caffe_root + 'python')\n",
-    "\n",
-    "import caffe\n",
-    "\n",
     "# Load the original network and extract the fully connected layers' parameters.\n",
     "net = caffe.Net('../models/bvlc_reference_caffenet/deploy.prototxt', \n",
     "                '../models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel', \n",