Final Experimental to stable Merge pull request #7 from AdrienJaugey/…

…experimental

Final Experimental to stable merge

.gitignore

@@ -10,6 +10,9 @@ results
 *.jp2
 *.txt
 *.h5
+!docs/img/*.png
+!docs/img/*.jpg
+!requirements.txt
 Mask_R_CNN_mAP_auto_script.py
 test.py
 bidouille.py

LICENSE

@@ -1,6 +1,8 @@
+Skinet (Segmentation of the Kidney through a Neural nETwork) Project
+
 MIT License
 
-Copyright (c) 2020 Adrien Jaugey
+Copyright (c) 2020 Skinet Team
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

LICENSE_MATTERPORT

@@ -0,0 +1,23 @@
+Mask R-CNN
+
+The MIT License (MIT)
+
+Copyright (c) 2017 Matterport, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.

Mask_R_CNN_ASAP_Annotations_Fusion.ipynb

@@ -0,0 +1,194 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "KqzoydcMBgc-"
+   },
+   "source": [
+    "# Mask R-CNN - ASAP Annotations Fusion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Tu0r49kND1_z"
+   },
+   "source": [
+    "## Initialisation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "fA4OVDl3D5zL"
+   },
+   "source": [
+    "### Detecting Environment"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1JnPwYerzUO4"
+   },
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "IN_COLAB = 'google.colab' in sys.modules\n",
+    "print(\"Executing in Google Colab\" if IN_COLAB else \"Executing locally\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "LXIK5fcSD9Xq"
+   },
+   "source": [
+    "### Getting all the needed files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "wa3F4QvMxmCE"
+   },
+   "outputs": [],
+   "source": [
+    "if IN_COLAB:\n",
+    "    import shutil\n",
+    "    shutil.rmtree('sample_data/', ignore_errors=True)\n",
+    "    import os\n",
+    "    GITHUB_REPO = \"https://raw.githubusercontent.com/AdrienJaugey/Custom-Mask-R-CNN-for-kidney-s-cell-recognition/experimental/\"\n",
+    "    files = ['mrcnn/TensorflowDetector.py', 'mrcnn/utils.py', 'mrcnn/visualize.py', 'mrcnn/post_processing.py',\n",
+    "             'mrcnn/Config.py', 'mrcnn/statistics.py', 'datasetTools/datasetDivider.py', 'common_utils.py',\n",
+    "             'datasetTools/datasetWrapper.py', 'datasetTools/datasetIsolator.py', 'datasetTools/AnnotationAdapter.py',\n",
+    "             'datasetTools/ASAPAdapter.py', 'datasetTools/LabelMeAdapter.py', 'datasetTools/CustomDataset.py']\n",
+    "    for fileToDownload in files:\n",
+    "        url = GITHUB_REPO + fileToDownload\n",
+    "        !wget -qN $url\n",
+    "        if '/' in fileToDownload:\n",
+    "            destDir = fileToDownload.split('/')[0]\n",
+    "            fileName = fileToDownload.split('/')[1].replace('/', '')\n",
+    "            os.makedirs(destDir, exist_ok=True)\n",
+    "            !mv $fileName $fileToDownload"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if IN_COLAB:\n",
+    "    from google.colab import drive\n",
+    "    drive.mount('/content/drive')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "w-I3GmFGEqUQ"
+   },
+   "source": [
+    "## Annotations fusion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from datasetTools import AnnotationAdapter\n",
+    "from datasetTools.ASAPAdapter import ASAPAdapter as a\n",
+    "from common_utils import progressBar"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Please set ```firstAnnotationsDir```, ```secondAnnotationsDir``` and ```outputAnnotationsDir``` before executing the cell."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "firstAnnotationsDir = \"annotations_in_1/\" #@param {type:\"string\"}\n",
+    "secondAnnotationsDir = \"annotations_in_2/\" #@param {type:\"string\"}\n",
+    "outputAnnotationsDir = \"annotations_out/\" #@param {type:\"string\"}\n",
+    "if IN_COLAB:\n",
+    "    firstAnnotationsDir = os.path.join('drive/MyDrive', firstAnnotationsDir)\n",
+    "    secondAnnotationsDir = os.path.join('drive/MyDrive', secondAnnotationsDir)\n",
+    "    outputAnnotationsDir = os.path.join('drive/MyDrive', outputAnnotationsDir)\n",
+    "firstAnnotationsDir = os.path.normpath(firstAnnotationsDir)\n",
+    "secondAnnotationsDir = os.path.normpath(secondAnnotationsDir)\n",
+    "outputAnnotationsDir = os.path.normpath(outputAnnotationsDir)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "Z6OOmdASyMvJ",
+    "pycharm": {
+     "name": "#%%\n"
+    },
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "firstDirList = os.listdir(firstAnnotationsDir)\n",
+    "secondDirList = os.listdir(secondAnnotationsDir)\n",
+    "files = [file for file in firstDirList if file in secondDirList]\n",
+    "total = len(files)\n",
+    "if not os.path.exists(outputAnnotationsDir):\n",
+    "    os.makedirs(outputAnnotationsDir)\n",
+    "for idx, file in enumerate(files):\n",
+    "    progressBar(idx + 1, total, prefix=\"Fusing annotations\", suffix=f\"Current file : {file}\")\n",
+    "    a.fuseAnnotationsFiles([os.path.join(folder, file) for folder in [firstAnnotationsDir, secondAnnotationsDir]],\n",
+    "                           os.path.join(outputAnnotationsDir, file))\n",
+    "print(\"\\nDone !\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "authorship_tag": "ABX9TyOHBS6d5l6TXpghydDsqc9D",
+   "collapsed_sections": [],
+   "name": "Mask_R_CNN_Stats_Extractor.ipynb",
+   "provenance": [],
+   "toc_visible": true
+  },
+  "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": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}