Merge branch 'master' into stage2_traited_script

Author: jonathanrocher

README.md

@@ -16,6 +16,10 @@ the process, attendees will learn how to design clean, maintainable and
 scalable applications, and package them into an installer.
 
 ## Set up instructions
+First step to set yourself up is to clone this repository
+```commandline
+git clone git@github.com:jonathanrocher/ets_tutorial.git
+```
 
 ### Requirements
 
@@ -37,6 +41,10 @@ edm shell -e ets_tutorial
 edm install pandas matplotlib traits traitsui scikits.image pillow pyqt5 ipython
 ```
 
+```commandline
+python etstool.py build
+```
+
 ### Conda users
 [TODO]
 
@@ -64,24 +72,24 @@ During the tutorial, don't hesitate to ask for help:
 
 ## Outline of the tutorial
 The tutorial will guide you through all the stages from a basic python script 
-(stage 0) to a fully packaged and installable application (stage 8). The 
+(stage 1) to a fully packaged and installable application (stage 8). The 
 included exercises will walk you through developing the primary product of 
-each stage. 
+each stage.
 A solution is available for each exercise, though, to ensure all participants 
 are able to reach the end goal.
 
-  - step 0: python script
-  - step 1: more robust script with ETS-Traits
-  - step 2: package management tools: etstool, unit test and CI [OPTIONAL]
+  - step 1: python script
+  - step 2: more robust script with ETS-Traits
   - step 3: GUI: first traitsUI views
   - step 4: pyface application: tree navigator and double-click on an image to 
     display the traitsUI view of the image.
-  - step 5: pyface application: 
+  - step 5: Fuller pyface application: 
     - add folder editor to display a table of metadata for all images inside
     - add button to launch the face detection on all images
     - add widgets to filter images
-  - step 6: pyface application (adaptation to build central pane editors) [OPTIONAL]
-  - step 7: pyface application: background run with traits-futures [OPTIONAL]
+  - INTERLUDE: code structure for scalability
+  - step 6: pyface application: adding menu and branding 
+  - step 7: pyface application: advanced features [OPTIONAL]
   - step 8: 1-click installer
 
 

ets_tutorial/util/mpl_figure_editor.py

@@ -1,7 +1,6 @@
 import matplotlib
 from matplotlib.backends.backend_qt5agg import (
-    FigureCanvasQTAgg as FigureCanvas,
-    NavigationToolbar2QT as NavigationToolbar
+        FigureCanvasQTAgg, NavigationToolbar2QT
 )
 from pyface.qt import QtGui
 from traitsui.api import BasicEditorFactory
@@ -15,21 +14,32 @@ class _MplFigureEditor(Editor):
     scrollable = True
 
     def init(self, parent):
+        """Create and initialize the underlying toolkit widget.
+        """
         self.set_tooltip()
-        self.control = self._create_mpl_canvas(parent)
+        self.control = QtGui.QWidget()
+        self.control.setLayout(QtGui.QVBoxLayout())
+        self._do_layout()
 
     def update_editor(self):
-        pass
-
-    def _create_mpl_canvas(self, parent):
-        control = QtGui.QWidget()
-        canvas = FigureCanvas(figure=self.value)
-        toolbar = NavigationToolbar(canvas, control)
-        layout = QtGui.QVBoxLayout()
+        """Updates the editor when the value changes externally to the editor.
+        """
+        self.clear_layout()
+        self._do_layout()
+
+    def _do_layout(self):
+        """Creates sub-widgets and does layout.
+        """
+        canvas = FigureCanvasQTAgg(figure=self.value)
+        # Allow the figure canvas to expand and shrink with the main widget.
+        canvas.setSizePolicy(
+            QtGui.QSizePolicy.Policy.Expanding,
+            QtGui.QSizePolicy.Policy.Expanding,
+        )
+        toolbar = NavigationToolbar2QT(canvas, self.control)
+        layout = self.control.layout()
         layout.addWidget(toolbar)
         layout.addWidget(canvas)
-        control.setLayout(layout)
-        return control
 
 
 class MplFigureEditor(BasicEditorFactory):

ets_tutorial/util/tests/test_mpl_figure_editor.py

@@ -14,6 +14,7 @@ class Plot(HasTraits):
 
     view = View(
         Item("figure", editor=MplFigureEditor(), show_label=False),
+        resizable=True
     )
 
     def _figure_default(self):

sample_images/20210802_191429.jpg

@@ -0,0 +1,61 @@
+""" Script analyzing an image, detecting human faces inside it, and printing
+EXIF data about it.
+"""
+from os.path import join
+
+import PIL.Image
+from PIL.ExifTags import TAGS
+from skimage import data
+from skimage.feature import Cascade
+import matplotlib.pyplot as plt
+import numpy as np
+from matplotlib import patches
+
+# Select image file -----------------------------------------------------------
+
+image_paths = [
+    join("..", "sample_images", "IMG-0311_xmas_2020.JPG"),
+    join("..", "sample_images", "owls.jpg")
+]
+
+# Load the trained file from the module root.
+trained_file = data.lbp_frontal_face_cascade_filename()
+
+# Initialize the detector cascade.
+detector = Cascade(trained_file)
+
+for path in image_paths:
+    img = PIL.Image.open(path)
+
+    img_metadata = {TAGS[k]: v for k, v in img._getexif().items() if k in TAGS}
+
+    # Detect faces ------------------------------------------------------------
+
+    detected = detector.detect_multi_scale(img=np.asarray(img),
+                                           scale_factor=1.2,
+                                           step_ratio=1,
+                                           min_size=(60, 60),
+                                           max_size=(600, 600))
+
+    img_metadata["Number of faces detected"] = len(detected)
+    print(img_metadata)
+
+    # Visualize results -------------------------------------------------------
+
+    plt.imshow(img)
+    img_desc = plt.gca()
+
+    for patch in detected:
+
+        img_desc.add_patch(
+            patches.Rectangle(
+                (patch['c'], patch['r']),
+                patch['width'],
+                patch['height'],
+                fill=False,
+                color='r',
+                linewidth=2
+            )
+        )
+
+    plt.show()

sample_images/owls.jpg

@@ -0,0 +1,3 @@
+# Second real version of the pycasa ETS pyface application!
+Building on the application state 4.2, this version simply adds an editor and a 
+view for a folder to be visualized.

stage0_starting_script/face_detect.py

@@ -0,0 +1,2 @@
+
+__version__ = "0.0.1"