New analysis result

analysis/extracts_images_zones.ipynb

@@ -0,0 +1,94 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from ipfml.processing.segmentation import divide_in_blocks\n",
+    "from PIL import Image\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "noisy_image_path = \"/home/jbuisine/Documents/Thesis/Development/thesis-data/SIN3D_HD_all_center/p3d_bathroom-view0_part6/p3d_bathroom-view0_00500.png\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reference_image_path = \"/home/jbuisine/Documents/Thesis/Development/thesis-data/SIN3D_HD_all_center/p3d_bathroom-view0_part6/p3d_bathroom-view0_10000.png\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "noisy_img = Image.open(noisy_image_path)\n",
+    "reference_img = Image.open(reference_image_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "noisy_blocks = divide_in_blocks(noisy_img, (200, 200), pil=True)\n",
+    "reference_blocks = divide_in_blocks(reference_img, (200, 200), pil=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "targeted_noisy_block = noisy_blocks[9]\n",
+    "targeted_reference_block = reference_blocks[9]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "targeted_noisy_block.save('noisy_block_10_bathroom.png')\n",
+    "targeted_reference_block.save('reference_block_10_bathroom.png')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.6.1 64-bit ('thesis-venv': venv)",
+   "language": "python",
+   "name": "python36164bitthesisvenvvenva88eb0ffd2f54d649db9e765b609711d"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

analysis/svd_entropy_analysis_convergence.ipynb

@@ -386,9 +386,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.0"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

analysis/svd_entropy_diff_analysis.ipynb

@@ -1022,9 +1022,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.0"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

analysis/svd_zones_analysis.ipynb

@@ -324,7 +324,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.0"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,