Merge branch 'master' of https://github.com/ESA-PhiLab/iris

README.md

@@ -20,7 +20,7 @@ cd iris
 python setup.py install
 ```
 
-If you are altering the IRIS source code then you made find it easier to install like below, to avoid having to reinstall it every time a change is made
+If you are altering the IRIS source code then you may find it easier to install like below, to avoid having to reinstall it every time a change is made
 ```
 pip install -e ./
 ```
@@ -34,12 +34,14 @@ Once installed, you can run the demo version of IRIS
 iris demo
 ```
 
-Having run the demo, you can then create a personalised config file, based on _demo/cloud-segmentation.json_. With your own config file, you can then instantiate your own custom project. <a href="https://github.com/ESA-PhiLab/iris/blob/master/docs/config.m">Here is a guide</a> on how to write your own config file.
+Having run the demo, you can then create a personalised config file, based on _demo/cloud-segmentation.json_. With your own config file, you can then instantiate your own custom project. <a href="https://github.com/ESA-PhiLab/iris/blob/master/docs/config.md">Here is a guide</a> on how to write your own config file.
 
 ```
 iris label <your-config-file>
 ```
 
+It is recommended to use a keyboard and mouse with scrollwheel for IRIS. Currently, control via trackpad is limited and awkward.
+
 ### Docker
 
 You can also use Docker to deploy IRIS. First, build an image (run from IRIS's root directory). Then, you can use docker run to launch IRIS. However, please note that port-forwarding is needed (here we use port 80 as an example for a typical http setup, but the port number can be set in your IRIS config file) and the directory to your project also needs to be given as a volume to docker.
@@ -49,5 +51,8 @@ docker build --tag iris .
 docker run -p 80:80 -v <dataset_path>:/dataset/ --rm -it iris label /dataset/cloud-segmentation.json
 ```
 
+### Run on Github Codespaces
+To run in a [Github codespace](https://docs.github.com/en/codespaces/overview) fork this repository, then in the Github UI select `Code/Codespaces/Open in codespace`. Run `pip install -e .` and then `iris demo`. You will see a popup that there is an app on port 5000, click the link to open a new window showing Iris 🎉
+
 
 **Visit the official iris Github page:  https://github.com/ESA-PhiLab/iris**

TODO.md

@@ -32,7 +32,7 @@
 - [ ] Add helper tips for each field on Preferences tab after ~1 second mouse hover
 - [ ] Add admin tab for data statistics visualisation over the whole dataset. E.g. class pie-chart, RF confusion matrix, input dimension importance, etc.
 - [ ] Add "iris export <options> PROJECT" command to save final versions of masks, and output some python-friendly (e.g. pandas) tables to look at dataset statistics
-
+- [ ] Add automatic config checker to spot common logic errors. Currently many typos/errors in config do not lead to a good error message.
 
 ### Big future plans:
 

iris/admin/__init__.py

@@ -2,6 +2,7 @@
 from datetime import timedelta
 
 import flask
+import markupsafe
 from sqlalchemy import func
 
 from iris.user import requires_admin, requires_auth
@@ -44,7 +45,7 @@ def users():
     users_json = [user.to_json() for user in users]
 
     html = flask.render_template('admin/users.html', users=users_json, order_by=order_by, ascending=ascending)
-    return flask.render_template('admin/index.html', user=user, page=flask.Markup(html))
+    return flask.render_template('admin/index.html', user=user, page=markupsafe.Markup(html))
 
 @admin_app.route('/actions/<type>', methods=['GET'])
 @requires_auth
@@ -74,7 +75,7 @@ def actions(type):
         'admin/actions.html', action_type=type, actions=actions_json,
         image_stats=image_stats, order_by=order_by, ascending=ascending
     )
-    return flask.render_template('admin/index.html', user=user, page=flask.Markup(html))
+    return flask.render_template('admin/index.html', user=user, page=markupsafe.Markup(html))
 
 @admin_app.route('/images', methods=['GET'])
 @requires_auth
@@ -117,4 +118,4 @@ def images():
     html = flask.render_template(
         'admin/images.html', images=images, order_by=order_by, ascending=ascending
     )
-    return flask.render_template('admin/index.html', user=user, page=flask.Markup(html))
+    return flask.render_template('admin/index.html', user=user, page=markupsafe.Markup(html))

iris/main/__init__.py

@@ -2,6 +2,7 @@
 import json
 
 import flask
+import markupsafe
 import numpy as np
 from PIL import Image as PILImage
 from skimage.transform import resize
@@ -92,7 +93,7 @@ def metadata(image_id):
 
     if flask.request.args.get('safe_html', False):
         metadata = {
-            k: flask.Markup(str(v))
+            k: markupsafe.Markup(str(v))
             for k, v in metadata.items()
         }
 

iris/project.py

@@ -10,6 +10,8 @@
 import re
 
 import flask
+import markupsafe
+
 import json
 from matplotlib import cm
 import numpy as np
@@ -95,7 +97,7 @@ def load_from(self, filename):
         # Make sure the HTML is understood in the descriptions:
         for name, view in self.config['views'].items():
             view['name'] = name
-            view['description'] = flask.Markup(
+            view['description'] = markupsafe.Markup(
                 view.get('description', view['name'])
             )
             view['stretch'] = view.get('stretch', 'linear')

iris/segmentation/__init__.py

@@ -272,7 +272,7 @@ def save_mask(image_id):
     # The user mask denotes who classified the pixels in the mask:
     #   if true: the user classified the pixel
     #   if false: the AI classified the pixel
-    user_mask = data[1+mask_length:-1].astype(np.bool)
+    user_mask = data[1+mask_length:-1].astype(bool)
     user_mask = user_mask.reshape(project['segmentation']['mask_shape'][::-1])
 
     final_mask_file, user_mask_file = get_mask_filenames(image_id, user_id)

iris/utils.py

@@ -1,7 +1,7 @@
 from copy import deepcopy
 
 import flask
-
+import markupsafe
 
 
 class View:
@@ -12,8 +12,8 @@ def __init__(self, name, description, loader):
 
     def to_json(self):
         return {
-            'name': flask.Markup(self.name),
-            'description': flask.Markup(self.description),
+            'name': markupsafe.Markup(self.name),
+            'description': markupsafe.Markup(self.description),
         }
 
 def merge_deep_dicts(d1, d2):

requirements.txt

@@ -1,8 +1,8 @@
-flask==2.2.2
+flask==2.3.2
 flask_compress==1.13
 flask-sqlalchemy==2.5.1
 numpy==1.23.4
-pyyaml==5.4.1
+pyyaml>=5.4.1
 lightgbm==3.3.3
 rasterio==1.3.3
 requests==2.28.1