Merge branch 'master' into update-readme

Makefile

@@ -13,3 +13,9 @@ run-tests:
 		docker-compose -f docker-compose.yml -f docker-compose.test.yml build image-quality
 	@env VERSION=${version-dev} PYTHON_DOCKER_VERSION=${python-docker-version} \
 		docker-compose -f docker-compose.yml -f docker-compose.test.yml run image-quality
+
+clean-notebooks:
+	echo "Cleaning notebooks"
+	find ./ -name "*.ipynb" | xargs python3 -m nbconvert --ClearOutputPreprocessor.enabled=True --inplace
+	echo "Removing checkpoints"
+	find . -type d -iname .ipynb_checkpoints -exec rm -r {} +

imquality/__init__.py

@@ -1 +1 @@
-__version__ = "1.2.5"
+__version__ = "1.2.5"

imquality/datasets/live_iqa.py

@@ -29,7 +29,7 @@
 distorted with different distortion types. These images were acquired in support of a research 
 project on generic shape matching and recognition.
 """
-URLS = ["https://live.ece.utexas.edu/research/quality/subjective.htm"]
+URL = u"https://live.ece.utexas.edu/research/quality/subjective.htm"
 LICENSE = """
 -----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------ 
 Copyright (c) 2003 The University of Texas at Austin 
@@ -70,7 +70,7 @@ def _info(self):
                 "dmos_realigned_std": tf.float32,
             }),
             supervised_keys=SUPERVISED_KEYS,
-            urls=URLS,
+            homepage=URL,
             citation=CITATION,
             redistribution_info={
                 'license': LICENSE,

imquality/datasets/tid2013.py

@@ -26,7 +26,7 @@
 organized in such a manner that they indicate a number of the reference image, 
 then a number of distortion's type, and, finally, a number of distortion's level: "iXX_YY_Z.bmp".
 """
-URLS = ["http://www.ponomarenko.info/tid2013.htm"]
+URL = u"http://www.ponomarenko.info/tid2013.htm"
 SUPERVISED_KEYS = ("distorted_image", "mos")
 
 
@@ -43,7 +43,7 @@ def _info(self):
                 "mos": tf.float32,
             }),
             supervised_keys=SUPERVISED_KEYS,
-            urls=URLS,
+            homepage=URL,
             citation=CITATION,
         )
 

notebooks/train-diqa-base.ipynb

@@ -5,17 +5,21 @@
    "execution_count": null,
    "metadata": {
     "pycharm": {
-     "is_executing": false,
      "name": "#%%\n"
     }
    },
    "outputs": [],
    "source": [
-    "import imageio\n",
-    "import random\n",
+    "!pip install --user \"image-quality[dataset]>=1.2.4\"\n",
+    "\n",
     "import tensorflow as tf\n",
     "from tensorflow.keras.layers import Conv2D, Dense, GlobalAveragePooling2D\n",
-    "from notebooks.utils import show_images, gaussian_filter, image_normalization, rescale, image_shape\n",
+    "from notebooks.utils import (\n",
+    "    show_images,\n",
+    "    gaussian_filter,\n",
+    "    image_normalization,\n",
+    "    rescale,\n",
+    "    image_shape)\n",
     "import imquality.datasets"
    ]
   },
@@ -163,8 +167,7 @@
     "pycharm": {
      "is_executing": false,
      "name": "#%%\n"
-    },
-    "scrolled": false
+    }
    },
    "outputs": [],
    "source": [
@@ -232,8 +235,7 @@
     "pycharm": {
      "is_executing": false,
      "name": "#%%\n"
-    },
-    "scrolled": false
+    }
    },
    "outputs": [],
    "source": [
@@ -587,9 +589,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "for epoch in range(1):\n",
@@ -746,16 +746,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
-  },
-  "pycharm": {
-   "stem_cell": {
-    "cell_type": "raw",
-    "metadata": {
-     "collapsed": false
-    },
-    "source": []
-   }
+   "version": "3.7.5"
   }
  },
  "nbformat": 4,