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Make whitespace consistent, change string formatting from modulo to format #22

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Make whitespace consistent, change string formatting from modulo to format #22

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18 changes: 9 additions & 9 deletions dream.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -93,7 +93,7 @@
"\n",
"net = caffe.Classifier('tmp.prototxt', param_fn,\n",
" mean = np.float32([104.0, 116.0, 122.0]), # ImageNet mean, training set dependent\n",
" channel_swap = (2,1,0)) # the reference model has channels in BGR order instead of RGB\n",
" channel_swap = (2, 1, 0)) # the reference model has channels in BGR order instead of RGB\n",
"\n",
"# a couple of utility functions for converting to and from Caffe's input image layout\n",
"def preprocess(net, img):\n",
Expand Down Expand Up @@ -194,7 +194,7 @@
" # prepare base images for all octaves\n",
" octaves = [preprocess(net, base_img)]\n",
" for i in xrange(octave_n-1):\n",
" octaves.append(nd.zoom(octaves[-1], (1, 1.0/octave_scale,1.0/octave_scale), order=1))\n",
" octaves.append(nd.zoom(octaves[-1], (1, 1.0/octave_scale, 1.0/octave_scale), order=1))\n",
" \n",
" src = net.blobs['data']\n",
" detail = np.zeros_like(octaves[-1]) # allocate image for network-produced details\n",
Expand All @@ -203,7 +203,7 @@
" if octave > 0:\n",
" # upscale details from the previous octave\n",
" h1, w1 = detail.shape[-2:]\n",
" detail = nd.zoom(detail, (1, 1.0*h/h1,1.0*w/w1), order=1)\n",
" detail = nd.zoom(detail, (1, 1.0*h/h1, 1.0*w/w1), order=1)\n",
"\n",
" src.reshape(1,3,h,w) # resize the network's input image size\n",
" src.data[0] = octave_base+detail\n",
Expand Down Expand Up @@ -416,7 +416,7 @@
"s = 0.05 # scale coefficient\n",
"for i in xrange(100):\n",
" frame = deepdream(net, frame)\n",
" PIL.Image.fromarray(np.uint8(frame)).save(\"frames/%04d.jpg\"%frame_i)\n",
" PIL.Image.fromarray(np.uint8(frame)).save(\"frames/{index}.jpg\".format(index = frame_i))\n",
" frame = nd.affine_transform(frame, [1-s,1-s,1], [h*s/2,w*s/2,0], order=1)\n",
" frame_i += 1"
],
Expand Down Expand Up @@ -511,7 +511,7 @@
"end = 'inception_3b/output'\n",
"h, w = guide.shape[:2]\n",
"src, dst = net.blobs['data'], net.blobs[end]\n",
"src.reshape(1,3,h,w)\n",
"src.reshape(1, 3, h, w)\n",
"src.data[0] = preprocess(net, guide)\n",
"net.forward(end=end)\n",
"guide_features = dst.data[0].copy()"
Expand All @@ -536,10 +536,10 @@
" x = dst.data[0].copy()\n",
" y = guide_features\n",
" ch = x.shape[0]\n",
" x = x.reshape(ch,-1)\n",
" y = y.reshape(ch,-1)\n",
" x = x.reshape(ch, -1)\n",
" y = y.reshape(ch, -1)\n",
" A = x.T.dot(y) # compute the matrix of dot-products with guide features\n",
" dst.diff[0].reshape(ch,-1)[:] = y[:,A.argmax(1)] # select ones that match best\n",
" dst.diff[0].reshape(ch, -1)[:] = y[:, A.argmax(1)] # select ones that match best\n",
"\n",
"_=deepdream(net, img, end=end, objective=objective_guide)"
],
Expand Down Expand Up @@ -575,4 +575,4 @@
"metadata": {}
}
]
}
}