Cpu eval2

.gitignore

@@ -19,7 +19,9 @@ plots/**
 # also keep all .gitkeep files
 !.gitkeep
 
-
+# ignore goturn caffe model 
+src/goturn.caffemodel 
+src/goturn.prototxt
 ##########################
 # Common files
 

conf/base/parameters.yml

@@ -11,7 +11,7 @@ static_pipeline:
   load_ref_file: False
   ref_file_name: "example_dataset"
   camera_list:
-    [   
+    [
       "00001.03601",
       "00001.07591",
       "00001.01252",
@@ -33,19 +33,31 @@ static_pipeline:
       "00001.04336",
       "00001.09560"
     ]
-  from_date: "2019-07-17" 
+  from_date: "2019-07-17"
   to_date: "2019-07-17"
   from_time: "00-00-00"
   to_time: "23-59-59"
+  chunk_size: 10
 
 data_renaming: # TODO: remove later when renaming finished
   old_path: "raw/video_data_new"
   new_path: "raw/videos"
   date_format: "%Y%m%d-%H%M%S"
 
+eval_pipeline_settings:
+  eval_ref_name: "annotated_videos"
+  eval_chunk_size: 5
+  eval_verbosity: True
+  eval_params_order: ['tracker_type', 'detection_model', "detection_frequency", "detection_iou_threshold", "stop_start_iou_threshold"]
+  eval_tracker_types: ['kcf', 'mosse', 'csrt', 'tld', 'boosting', 'mil']
+  eval_detection_models: ['yolov3-tiny', 'yolov3']
+  eval_detection_frequency: [4, 6]
+  eval_detection_iou_threshold: [0.2, 0.3, 0.4, 0.5]
+  eval_stop_start_iou_threshold: [0.75, 0.80, 0.85, 0.90]
+
 modelling:
   # obj detection
-  detection_model: "yolov3-tiny"
+  default_detection_model: "yolov3_tf"
   detection_implementation: "cvlib"
   detection_iou_threshold: 0.05
   detection_confidence_threshold: 0.2
@@ -54,7 +66,7 @@ modelling:
 
   # tracking
   selected_labels: ["car", "truck", "bus", "motorbike"]
-  opencv_tracker_type: "csrt"
+  default_tracker_type: "csrt"
   iou_threshold: 0.05 #controls how much two objects' bboxes must overlap to be considered the "same"
   detection_frequency: 4
   skip_no_of_frames: 3
@@ -65,7 +77,6 @@ modelling:
   stop_start_iou_threshold: 0.80
 
 reporting:
-  chunk_size: 10
   dtype:
     camera_id: 'category'
   video_level_column_order: ["camera_id", "video_upload_datetime", "vehicle_type", "counts", "starts", "stops", "parked"]

conf/base/paths.yml

@@ -1,12 +1,12 @@
 s3_paths:
   bucket_name: "air-pollution-uk" #s3 bucket name
   s3_video: "raw/videos/" #path to video data in s3 bucket
-  s3_annotations: "ref/annotations/"
+  s3_cvat_annotations: "ref/annotations/cvat/"
   s3_video_names: "ref/video_names/"
   s3_camera_details: "ref/camera_details/camera_details.json"
 
   s3_frame_level: "frame_level/" # TODO DELETE THIS
-  s3_profile: "dssg" # TODO: change this for user? 
+  s3_profile: "dssg" # TODO: change this for user?
   s3_creds: "dev_s3" # TODO: CHANGE TO JUST S3
   s3_detection_model: "ref/model_conf/"
 
@@ -29,3 +29,9 @@ db_paths:
   db_name: "airquality"
   db_frame_level: 'frame_stats'
   db_video_level: 'video_stats'
+
+  eval_db_frame_level_prefix: 'frame_stats'
+  eval_db_video_level_prefix: 'video_stats'
+  eval_db_video_stats: "eval_video_performance_test"
+  eval_db_video_diffs: "eval_video_diffs_test"
+  eval_db_frame_stats: "eval_frame_stats_test"

notebooks/20190617-jch-exploring-folium.ipynb

@@ -11,15 +11,13 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import folium\n",
     "import boto3\n",
     "import pandas as pd\n",
-    "% matplotlib inline"
+    "%matplotlib inline"
    ]
   },
   {
@@ -37,10 +35,10 @@
     {
      "data": {
       "text/html": [
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+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;charset=utf-8;base64,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\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
       ],
       "text/plain": [
-       "<folium.folium.Map at 0x160ce299b70>"
+       "<folium.folium.Map at 0x26f33705b38>"
       ]
      },
      "execution_count": 3,
@@ -53,7 +51,7 @@
     "londonmap = folium.Map(\n",
     "    width=500, height=500,\n",
     "    location = London,\n",
-    "    zoom_start = 12, \n",
+    "    zoom_start = 12, t\n",
     "    tiles = 'stamentoner')\n",
     "\n",
     "londonmap"
@@ -68,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -159,7 +157,7 @@
        "4           4  00/006  531648.94  180896.39  -0.104276  51.511665"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -217,7 +215,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -290,7 +288,7 @@
        "4       Cromwell_Rd/Earls_Court_Rd   51.4946   -0.19570"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -307,7 +305,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -325,7 +323,7 @@
        " [51.3741, -0.09646]]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -338,16 +336,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "C:/Users/joh3146/Documents/dssg/map_data_locations_small.html\n",
-      "C:/Users/joh3146/Documents/dssg/map_data_locations_regular.html\n",
-      "C:/Users/joh3146/Documents/dssg/map_data_locations_large.html\n"
+      "C:/Users/Caroline Wang/Onedrive/DSSG/map_data_location_smalls.pdf\n",
+      "C:/Users/Caroline Wang/Onedrive/DSSG/map_data_location_regulars.pdf\n",
+      "C:/Users/Caroline Wang/Onedrive/DSSG/map_data_location_larges.pdf\n"
      ]
     }
    ],
@@ -362,13 +360,13 @@
     "        zoom_start = 20, \n",
     "        tiles = 'stamentoner')\n",
     "\n",
-    "    for point in range(0, len(tims_location_list)):\n",
-    "        folium.CircleMarker(tims_location_list[point],\n",
-    "                            radius=labelsizes[tick],\n",
-    "                            color='red',\n",
-    "                            fill_color='red',\n",
-    "                            fill_opacity=0.2\n",
-    "                           ).add_to(london_map)\n",
+    "#     for point in range(0, len(tims_location_list)):\n",
+    "#         folium.CircleMarker(tims_location_list[point],\n",
+    "#                             radius=labelsizes[tick],\n",
+    "#                             color='red',\n",
+    "#                             fill_color='red',\n",
+    "#                             fill_opacity=0.2\n",
+    "#                            ).add_to(london_map)\n",
     "\n",
     "    for point in range(0, len(jc_location_list)):\n",
     "        folium.CircleMarker(jc_location_list[point],\n",
@@ -378,10 +376,10 @@
     "                            fill_opacity=0.2\n",
     "                           ).add_to(london_map)\n",
     "    \n",
-    "    filestr_in = \"C:/Users/joh3146/Documents/dssg/map_data_locations.html\"\n",
+    "    filestr_in = \"C:/Users/Caroline Wang/Onedrive/DSSG/map_data_locations.html\"\n",
     "    filestr_out = filestr_in[:-5] + '_' + labelstr[tick] + filestr_in[-5:]\n",
     "    print(filestr_out)\n",
-    "    london_map.save(\"C:/Users/joh3146/Documents/dssg/london_map_large_labels.html\")"
+    "    london_map.save(filestr_out)\n"
    ]
   }
  ],

notebooks/20190701-jch-jamcam-selection.ipynb

@@ -1257,7 +1257,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,