Merge branch 'master' of http://git.normalized.xyz/Florent/LD2DAPs

Notebooks/Kernel Density Estimation.ipynb

@@ -0,0 +1,186 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "from pathlib import Path\n",
+    "import numpy as np\n",
+    "from scipy import stats\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "triskele_path = Path('../triskele/python/')\n",
+    "sys.path.append(str(triskele_path.resolve()))\n",
+    "import triskele\n",
+    "\n",
+    "# Specific Utils\n",
+    "\n",
+    "def DFC_filter(raster):\n",
+    "    raster[raster > 1e4] = raster[raster < 1e4].max()\n",
+    "\n",
+    "def show(im, im_size=1, save=None):\n",
+    "    plt.figure(figsize=(16*im_size,3*im_size))\n",
+    "    plt.imshow(im)\n",
+    "    plt.colorbar()\n",
+    "    \n",
+    "    if save is not None:\n",
+    "        plt.savefig(save, bbox_inches='tight', pad_inches=1)\n",
+    "    \n",
+    "    plt.show()\n",
+    "\n",
+    "def mshow(Xs, titles=None, im_size=1, save=None):\n",
+    "    s = len(Xs)\n",
+    "\n",
+    "    plt.figure(figsize=(16*im_size,3*im_size*s))\n",
+    "\n",
+    "    for i in range(s):\n",
+    "        plt.subplot(s,1,i+1)\n",
+    "        plt.imshow(Xs[i])\n",
+    "        \n",
+    "        if titles is not None:\n",
+    "            plt.title(titles[i])\n",
+    "            \n",
+    "        plt.colorbar()\n",
+    "    \n",
+    "    if save is not None:\n",
+    "        plt.savefig(save, bbox_inches='tight', pad_inches=1)\n",
+    "        \n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Kernel Density Estimation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "raster = triskele.read('../Data/test.tiff')\n",
+    "show(raster)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kernel = stats.gaussian_kde(raster.reshape(-1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "\n",
+    "test = cv2.imread('/home/florent/Pictures/Jura-Panorama.jpg')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bins = [x for x in range(100)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kernel.pdf(bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.plot(bins, kernel.pdf(bins))\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "show(test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kB = stats.gaussian_kde(test[:,:,0].reshape(-1))\n",
+    "kG = stats.gaussian_kde(test[:,:,1].reshape(-1))\n",
+    "kR = stats.gaussian_kde(test[:,:,2].reshape(-1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bins = [x for x in range(255)]\n",
+    "plt.plot(bins, kB.pdf(bins))\n",
+    "plt.plot(bins, kG.pdf(bins))\n",
+    "plt.plot(bins, kR.pdf(bins))\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bins = [x for x in range(10)]\n",
+    "plt.plot(bins, kB.pdf(bins))\n",
+    "plt.plot(bins, kG.pdf(bins))\n",
+    "plt.plot(bins, kR.pdf(bins))\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "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"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

ld2dap/AttributeProfiles.py

@@ -12,6 +12,7 @@ from core import Filter
 
 ## TODO: dep
 import sys
+import numpy as np
 sys.path.append('../triskele/python')
 import triskele
 
@@ -31,4 +32,6 @@ class AttributeProfiles(Filter):
                               standard_deviation=self.sd,
                               moment_of_inertia=self.moi)
 
-        return att, None
+        att = np.dstack((att_min, att_max))
+
+        return att, metadata

ld2dap/LoadTIFF.py

@@ -8,7 +8,7 @@
 #
 # TODO details
 
-from core import Input
+from core import Input, Stack
 import numpy as np
 
 ## TODO: dep
@@ -23,10 +23,15 @@ class LoadTIFF(Input):
 
     def _process(self, data, metadata):
         layers = list()
+        metadata = list()
 
-        for file in self.files:
+        for i, file in enumerate(self.files):
             print('Loading {}'.format(file))
             layers.append(triskele.read(file))
+            metadata.append(Stack(i, desc=file, symb='I_{{{}}}'.format(i)))
 
-        return np.stack(layers, axis=2), self.files
+        return np.stack(layers, axis=2), metadata
+
+    def I(self, i):
+        return self.files[i]
 

ld2dap/SaveFig.py

@@ -0,0 +1,31 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+# \file SaveFig.py
+# \brief TODO
+# \author Florent Guiotte <florent.guiotte@gmail.com>
+# \version 0.1
+# \date 09 avril 2018
+#
+# TODO details
+
+from core import Output
+
+import matplotlib.pyplot as plt
+
+class SaveFig(Output):
+    def __init__(self, fname, bbox_inches='tight', pad_inches=1):
+        super().__init__(self.__class__.__name__)
+        self.fname       = fname
+        self.bbox_inches = bbox_inches
+        self.pad_inches  = pad_inches
+
+    def _process(self, data, metadata):
+        im_size = 2
+        fig = plt.figure(figsize=(16*im_size,3*im_size))
+        f1 = fig.add_subplot(111)
+        img = f1.imshow(data[:,:,-1])
+        plt.colorbar(img)
+        if metadata is not None:
+            f1.set_title(metadata[-1])
+        fig.savefig(self.fname, bbox_inches=self.bbox_inches, pad_inches=self.pad_inches)
+        plt.close(fig)

ld2dap/ShowFig.py

@@ -0,0 +1,31 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+# \file SaveFig.py
+# \brief TODO
+# \author Florent Guiotte <florent.guiotte@gmail.com>
+# \version 0.1
+# \date 09 avril 2018
+#
+# TODO details
+
+from core import Output
+
+import matplotlib.pyplot as plt
+
+class ShowFig(Output):
+    def __init__(self, fname, bbox_inches='tight', pad_inches=1):
+        super().__init__(self.__class__.__name__)
+        self.fname       = fname
+        self.bbox_inches = bbox_inches
+        self.pad_inches  = pad_inches
+
+    def _process(self, data, metadata):
+        im_size = 2
+        fig = plt.figure(figsize=(16*im_size,3*im_size))
+        f1 = fig.add_subplot(111)
+        img = f1.imshow(data[:,:,-1])
+        plt.colorbar(img)
+        if metadata is not None:
+            f1.set_title(metadata[-1])
+        plt.show()
+        plt.close(fig)

ld2dap/Treshold.py

@@ -0,0 +1,23 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+# \file Treshold.py
+# \brief TODO
+# \author Florent Guiotte <florent.guiotte@gmail.com>
+# \version 0.1
+# \date 09 avril 2018
+#
+# TODO details
+
+from core import Filter
+
+class Treshold(Filter):
+    def __init__(self, treshold, max_value=None):
+        super().__init__(self.__class__.__name__)
+        self.treshold  = treshold
+        self.max_value = max_value #if max_value is not None else treshold
+
+    def _process(self, data, metadata):
+        if self.max_value is None:
+            self.max_value = data[data < self.treshold].max()
+
+        return data * (data < self.treshold) + self.max_value * (data >= self.treshold), metadata

ld2dap/core/Node.py

@@ -17,7 +17,7 @@ class Node(object):
         return ("Node:{}".format(self.name))
 
     def process(self, data, metadata=None):
-        self._process(data)
+        self._process(data, metadata)
 
     def _process(self, data, metadata=None):
         raise NotImplementedError(

ld2dap/core/Stack.py

@@ -0,0 +1,23 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+# \file %filename%.py
+# \brief TODO
+# \author Florent Guiotte <florent.guiotte@gmail.com>
+# \version 0.1
+# \date 11 avril 2018
+#
+# TODO details
+
+
+class Stack(object):
+    def __init__(self, begin=0, size=1, desc=None, symb=None) :
+        self.begin = begin 
+        self.end   = begin + size 
+        self.desc  = list()
+        self.symb  = list()
+
+        if desc is not None:
+            self.desc.append(desc)
+
+        if symb is not None:
+            self.symb.append(symb)

ld2dap/core/__init__.py

@@ -11,3 +11,4 @@
 from .Output import Output
 from .Input import Input
 from .Filter import Filter
+from .Stack import Stack

ld2dap/test.py

@@ -8,19 +8,28 @@
 #
 # TODO details
 
-from core import Input, Output, Filter
+#from core import Input, Output, Filter
 from LoadTIFF import LoadTIFF
 from AttributeProfiles import AttributeProfiles as APs
+from SaveFig import SaveFig
+from Treshold import Treshold
+from ShowFig import ShowFig
+
+import numpy as np
 
 def main():
-    i = LoadTIFF(['../Data/test.tiff'])
+    i = LoadTIFF(['../Data/test.tiff', '../Data/test.tiff'])
-    ap = APs()
+    t = Treshold(1e4)
-    o = Output('o')
+    ap = APs(np.array([100,1e3,1e4]))
+    o = SaveFig('test.png')
+    s = ShowFig(None)
 
-    ap.input = i
+    t.input = i
-    o.input = i
+    ap.input = t
+    o.input = ap
+    s.input = ap
 
-    o.run()
+    i.run()
 
 if __name__ == '__main__':
     main()