Created
July 16, 2019 12:53
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Pyrdown bugreport
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"%matplotlib inline\n", | |
"import kornia\n", | |
"import torch\n", | |
"import math\n", | |
"import matplotlib.pyplot as plt\n", | |
"import numpy as np\n", | |
"from skimage.transform import pyramid_gaussian" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 29, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<matplotlib.image.AxesImage at 0x7f4ea5c4af28>" | |
] | |
}, | |
"execution_count": 29, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": "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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"timg = torch.zeros(1,1,64,32)\n", | |
"timg[0,0,32-10:32+10,16-10:16+10] = 1.0\n", | |
"img = kornia.utils.tensor_to_image(timg)[0,:,:,0]\n", | |
"plt.imshow(img)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 33, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": "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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
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}, | |
"output_type": "display_data" | |
}, | |
{ | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": "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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"pyramid = tuple(pyramid_gaussian(img, downscale=2, max_layer=4, multichannel=False))\n", | |
"plt.close('all')\n", | |
"for i in range(len(pyramid)):\n", | |
" plt.figure()\n", | |
" plt.imshow(pyramid[i])" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 34, | |
"metadata": { | |
"scrolled": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": "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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": "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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"plain_pyr = [timg]\n", | |
"for i in range(4):\n", | |
" plain_pyr.append(kornia.pyrdown(plain_pyr[-1]))\n", | |
"\n", | |
"plt.close('all')\n", | |
"for i in range(len(plain_pyr)):\n", | |
" plt.figure()\n", | |
" plt.imshow(plain_pyr[i].data.cpu().numpy()[0,0])" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 45, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": "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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
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"output_type": "display_data" | |
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{ | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
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"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": "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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"def _get_pyramid_gaussian_kernel() -> torch.Tensor:\n", | |
" \"\"\"Utility function that return a pre-computed gaussian kernel.\"\"\"\n", | |
" return torch.tensor([[\n", | |
" [1., 4., 6., 4., 1.],\n", | |
" [4., 16., 24., 16., 4.],\n", | |
" [6., 24., 36., 24., 6.],\n", | |
" [4., 16., 24., 16., 4.],\n", | |
" [1., 4., 6., 4., 1.]\n", | |
" ]]) / 256.\n", | |
"\n", | |
"class PyrDownFix(nn.Module):\n", | |
" r\"\"\"Blurs a tensor and downsamples it.\n", | |
"\n", | |
" Args:\n", | |
" borde_type (str): the padding mode to be applied before convolving.\n", | |
" The expected modes are: ``'constant'``, ``'reflect'``,\n", | |
" ``'replicate'`` or ``'circular'``. Default: ``'reflect'``.\n", | |
"\n", | |
" Return:\n", | |
" torch.Tensor: the downsampled tensor.\n", | |
"\n", | |
" Shape:\n", | |
" - Input: :math:`(B, C, H, W)`\n", | |
" - Output: :math:`(B, C, H / 2, W / 2)`\n", | |
"\n", | |
" Examples:\n", | |
" >>> input = torch.rand(1, 2, 4, 4)\n", | |
" >>> output = kornia.transform.PyrDown()(input) # 1x2x2x2\n", | |
" \"\"\"\n", | |
"\n", | |
" def __init__(self, border_type: str = 'reflect') -> None:\n", | |
" super(PyrDownFix, self).__init__()\n", | |
" self.border_type: str = border_type\n", | |
" self.kernel: torch.Tensor = _get_pyramid_gaussian_kernel()\n", | |
"\n", | |
" def forward(self, input: torch.Tensor) -> torch.Tensor: # type: ignore\n", | |
" if not torch.is_tensor(input):\n", | |
" raise TypeError(\"Input type is not a torch.Tensor. Got {}\"\n", | |
" .format(type(input)))\n", | |
" if not len(input.shape) == 4:\n", | |
" raise ValueError(\"Invalid input shape, we expect BxCxHxW. Got: {}\"\n", | |
" .format(input.shape))\n", | |
" # blur image\n", | |
" x_blur: torch.Tensor = kornia.filter2D(\n", | |
" input, self.kernel, self.border_type)\n", | |
"\n", | |
" return F.avg_pool2d(x_blur, 2,2)\n", | |
"plain_pyr_fix = [timg]\n", | |
"for i in range(4):\n", | |
" plain_pyr_fix.append(PyrDownFix()(plain_pyr_fix[-1]))\n", | |
"\n", | |
"plt.close('all')\n", | |
"for i in range(len(plain_pyr_fix)):\n", | |
" plt.figure()\n", | |
" plt.imshow(plain_pyr_fix[i].data.cpu().numpy()[0,0])" | |
] | |
} | |
], | |
"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": "3.7.3" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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