X-Git-Url: https://gerrit.akraino.org/r/gitweb?a=blobdiff_plain;f=example-apps%2FPDD%2Fpcb-defect-detection%2Fdata%2Flib_coco%2FPythonAPI%2FpycocoEvalDemo.ipynb;fp=example-apps%2FPDD%2Fpcb-defect-detection%2Fdata%2Flib_coco%2FPythonAPI%2FpycocoEvalDemo.ipynb;h=0000000000000000000000000000000000000000;hb=3ed2c61d9d7e7916481650c41bfe5604f7db22e9;hp=8b2ff0832b8a66ef43123e6ad2bc11e5a24ff2ef;hpb=e6d40ddb2640f434a9d7d7ed99566e5e8fa60cc1;p=ealt-edge.git

diff --git a/example-apps/PDD/pcb-defect-detection/data/lib_coco/PythonAPI/pycocoEvalDemo.ipynb b/example-apps/PDD/pcb-defect-detection/data/lib_coco/PythonAPI/pycocoEvalDemo.ipynb
deleted file mode 100755
index 8b2ff08..0000000
--- a/example-apps/PDD/pcb-defect-detection/data/lib_coco/PythonAPI/pycocoEvalDemo.ipynb
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@@ -1,168 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt\n",
-    "from pycocotools.coco import COCO\n",
-    "from pycocotools.cocoeval import COCOeval\n",
-    "import numpy as np\n",
-    "import skimage.io as io\n",
-    "import pylab\n",
-    "pylab.rcParams['figure.figsize'] = (10.0, 8.0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Running demo for *bbox* results.\n"
-     ]
-    }
-   ],
-   "source": [
-    "annType = ['segm','bbox','keypoints']\n",
-    "annType = annType[1]      #specify type here\n",
-    "prefix = 'person_keypoints' if annType=='keypoints' else 'instances'\n",
-    "print 'Running demo for *%s* results.'%(annType)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "loading annotations into memory...\n",
-      "Done (t=8.01s)\n",
-      "creating index...\n",
-      "index created!\n"
-     ]
-    }
-   ],
-   "source": [
-    "#initialize COCO ground truth api\n",
-    "dataDir='../'\n",
-    "dataType='val2014'\n",
-    "annFile = '%s/annotations/%s_%s.json'%(dataDir,prefix,dataType)\n",
-    "cocoGt=COCO(annFile)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Loading and preparing results...     \n",
-      "DONE (t=0.05s)\n",
-      "creating index...\n",
-      "index created!\n"
-     ]
-    }
-   ],
-   "source": [
-    "#initialize COCO detections api\n",
-    "resFile='%s/results/%s_%s_fake%s100_results.json'\n",
-    "resFile = resFile%(dataDir, prefix, dataType, annType)\n",
-    "cocoDt=cocoGt.loadRes(resFile)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "imgIds=sorted(cocoGt.getImgIds())\n",
-    "imgIds=imgIds[0:100]\n",
-    "imgId = imgIds[np.random.randint(100)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Running per image evaluation...      \n",
-      "DONE (t=0.46s).\n",
-      "Accumulating evaluation results...   \n",
-      "DONE (t=0.38s).\n",
-      " Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.505\n",
-      " Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.697\n",
-      " Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.573\n",
-      " Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.586\n",
-      " Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.519\n",
-      " Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.501\n",
-      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.387\n",
-      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.594\n",
-      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.595\n",
-      " Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.640\n",
-      " Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.566\n",
-      " Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.564\n"
-     ]
-    }
-   ],
-   "source": [
-    "# running evaluation\n",
-    "cocoEval = COCOeval(cocoGt,cocoDt,annType)\n",
-    "cocoEval.params.imgIds  = imgIds\n",
-    "cocoEval.evaluate()\n",
-    "cocoEval.accumulate()\n",
-    "cocoEval.summarize()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 2",
-   "language": "python",
-   "name": "python2"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 2
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.10"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}