Merge pull request #67 from jonathanrocher/fix/stage6_models

Fix: stage6 models

Author: jonathanrocher

stage6_branded_application/pycasa/model/image_file.py

@@ -1,16 +1,17 @@
 # General imports
-import os
+from os.path import splitext
 import PIL.Image
 from PIL.ExifTags import TAGS
 from skimage import data
 from skimage.feature import Cascade
 import numpy as np
 
 # ETS imports
-from traits.api import Array, cached_property, Dict, File, HasStrictTraits, \
-    List, Property
+from traits.api import (
+    Array, cached_property, Dict, File, HasStrictTraits, List, Property
+)
 
-SUPPORTED_FORMATS = [".png", ".jpg", ".jpeg"]
+SUPPORTED_FORMATS = [".png", ".jpg", ".jpeg", ".PNG", ".JPG", ".JPEG"]
 
 
 class ImageFile(HasStrictTraits):
@@ -24,43 +25,40 @@ class ImageFile(HasStrictTraits):
 
     faces = List
 
-    def to_array(self):
-        file_ext = os.path.splitext(self.filepath)[1].lower()
-        if not self.filepath or file_ext not in SUPPORTED_FORMATS:
-            return np.array([])
-
-        with PIL.Image.open(self.filepath) as img:
-            return np.asarray(img)
+    def _is_valid_file(self):
+        return (
+            bool(self.filepath) and
+            splitext(self.filepath)[1].lower() in SUPPORTED_FORMATS
+        )
 
     @cached_property
     def _get_data(self):
-        return self.to_array()
+        if not self._is_valid_file():
+            return np.array([])
+        with PIL.Image.open(self.filepath) as img:
+            return np.asarray(img)
 
     @cached_property
     def _get_metadata(self):
-        file_ext = os.path.splitext(self.filepath)[1].lower()
-        if not self.filepath or file_ext not in SUPPORTED_FORMATS:
+        if not self._is_valid_file():
             return {}
-
         with PIL.Image.open(self.filepath) as img:
             exif = img._getexif()
-
-        if exif:
-            return {TAGS[k]: v for k, v in exif.items()
-                    if k in TAGS}
-        else:
+        if not exif:
             return {}
+        return {TAGS[k]: v for k, v in exif.items() if k in TAGS}
 
-    def detect_faces(self, scale_factor=1.2, step_ratio=1, min_size=60,
-                     max_size=600):
-        """ Detect faces in the image.
-        """
+    def detect_faces(self):
+        # Load the trained file from the module root.
         trained_file = data.lbp_frontal_face_cascade_filename()
+
+        # Initialize the detector cascade.
         detector = Cascade(trained_file)
-        faces = detector.detect_multi_scale(img=self.data,
-                                            scale_factor=scale_factor,
-                                            step_ratio=step_ratio,
-                                            min_size=(min_size, min_size),
-                                            max_size=(max_size, max_size))
-        self.faces = faces
-        return faces
+
+        detected = detector.detect_multi_scale(img=self.data,
+                                               scale_factor=1.2,
+                                               step_ratio=1,
+                                               min_size=(60, 60),
+                                               max_size=(600, 600))
+        self.faces = detected
+        return self.faces

stage6_branded_application/pycasa/model/image_folder.py

@@ -1,24 +1,28 @@
 # General imports
-import os
+import glob
+from os.path import basename, expanduser, isdir
 
-import pandas as pd
 import numpy as np
+import pandas as pd
 
 # ETS imports
-from traits.api import Directory, Event, HasStrictTraits, Instance
+from traits.api import (
+    Directory, Event, HasStrictTraits, Instance, List, observe,
+)
 
 # Local imports
-from .image_file import ImageFile, SUPPORTED_FORMATS
+from pycasa.model.image_file import ImageFile, SUPPORTED_FORMATS
 
 FILENAME_COL = "filename"
-
 NUM_FACE_COL = "Num. faces"
 
 
 class ImageFolder(HasStrictTraits):
-    """ Model to hold an image folder.
+    """ Model for a folder of images.
     """
-    path = Directory
+    directory = Directory(expanduser("~"))
+
+    images = List(Instance(ImageFile))
 
     data = Instance(pd.DataFrame)
 
@@ -27,39 +31,39 @@ class ImageFolder(HasStrictTraits):
     def __init__(self, **traits):
         # Don't forget this!
         super(ImageFolder, self).__init__(**traits)
-        if not os.path.isdir(self.path):
-            msg = f"Unable to create an ImageFolder from {self.path} since" \
-                  f" it is not a valid directory."
+        if not isdir(self.directory):
+            msg = f"The provided directory isn't a real directory: " \
+                  f"{self.directory}"
             raise ValueError(msg)
+        self.data = self._create_metadata_df()
 
-        self.data = self.to_dataframe()
+    @observe("directory")
+    def _update_images(self, event):
+        self.images = [
+            ImageFile(filepath=file)
+            for fmt in SUPPORTED_FORMATS
+            for file in glob.glob(f"{self.directory}/*{fmt}")
+        ]
 
-    def to_dataframe(self):
-        if not self.path:
-            return pd.DataFrame({FILENAME_COL: [], NUM_FACE_COL: []})
+    @observe("images.items")
+    def _update_metadata(self, event):
+        self.data = self._create_metadata_df()
 
-        data = []
-        for filename in os.listdir(self.path):
-            file_ext = os.path.splitext(filename)[1].lower()
-            if file_ext in SUPPORTED_FORMATS:
-                filepath = os.path.join(self.path, filename)
-                img_file = ImageFile(filepath=filepath)
-                file_data = {FILENAME_COL: filename, NUM_FACE_COL: np.nan}
-                try:
-                    file_data.update(img_file.metadata)
-                except Exception:
-                    pass
-                data.append(file_data)
+    def _create_metadata_df(self):
+        if not self.images:
+            return pd.DataFrame({FILENAME_COL: [], NUM_FACE_COL: []})
+        return pd.DataFrame([
+                {
+                    FILENAME_COL: basename(img.filepath),
+                    NUM_FACE_COL: np.nan,
+                    **img.metadata
 
-        return pd.DataFrame(data)
+                }
+                for img in self.images
+        ])
 
     def compute_num_faces(self, **kwargs):
-        cols = list(self.data.columns)
-        for i, filename in enumerate(self.data[FILENAME_COL]):
-            print(filename)
-            filepath = os.path.join(self.path, filename)
-            img_file = ImageFile(filepath=filepath)
-            faces = img_file.detect_faces(**kwargs)
-            j = cols.index(NUM_FACE_COL)
-            self.data.iloc[i, j] = len(faces)
+        for i, image in enumerate(self.images):
+            faces = image.detect_faces(**kwargs)
+            self.data[NUM_FACE_COL].iat[i] = len(faces)
             self.data_updated = True

stage6_branded_application/pycasa/model/tests/test_image_file.py

@@ -18,31 +18,28 @@ class TestImageFile(TestCase):
     def test_no_image_file(self):
         img = ImageFile()
         self.assertEqual(img.metadata, {})
-        data = img.to_array()
-        self.assertIsInstance(data, np.ndarray)
-        self.assertEqual(data.shape, (0,))
+        self.assertIsInstance(img.data, np.ndarray)
+        self.assertEqual(img.data.shape, (0,))
 
     def test_bad_type_image_file(self):
         img = ImageFile(filepath=__file__)
         self.assertEqual(img.metadata, {})
-        data = img.to_array()
-        self.assertIsInstance(data, np.ndarray)
-        self.assertEqual(data.shape, (0,))
+        self.assertIsInstance(img.data, np.ndarray)
+        self.assertEqual(img.data.shape, (0,))
 
     def test_image_metadata(self):
         img = ImageFile(filepath=SAMPLE_IMG1)
         self.assertNotEqual(img.metadata, {})
         for key in ['ExifVersion', 'ExifImageWidth', 'ExifImageHeight']:
             self.assertIn(key, img.metadata.keys())
-        data = img.to_array()
         expected_shape = (img.metadata['ExifImageHeight'],
                           img.metadata['ExifImageWidth'], 3)
-        self.assertEqual(data.shape, expected_shape)
+        self.assertEqual(img.data.shape, expected_shape)
 
     def test_image_data(self):
         img = ImageFile(filepath=SAMPLE_IMG1)
         self.assertNotIn(0, img.data.shape)
-        np.testing.assert_almost_equal(img.data, img.to_array())
+        np.testing.assert_almost_equal(img.data, img.data)
         self.assertIsInstance(img.data, np.ndarray)
         self.assertNotEqual(img.data.mean(), 0)
 

stage6_branded_application/pycasa/model/tests/test_image_folder.py

@@ -17,21 +17,19 @@
 class TestImageFolder(TestCase):
     def test_no_folder(self):
         with self.assertRaises(ValueError):
-            ImageFolder()
+            ImageFolder(directory="path/to/nonexistent/dir")
 
     def test_with_file(self):
         with self.assertRaises(ValueError):
-            ImageFolder(path=__file__)
+            ImageFolder(directory=__file__)
 
     def test_empty_folder(self):
-        img = ImageFolder(path=HERE)
-        data = img.to_dataframe()
-        self.assertIsInstance(data, pd.DataFrame)
-        self.assertEqual(len(data), 0)
+        img_folder = ImageFolder(directory=HERE)
+        self.assertIsInstance(img_folder.data, pd.DataFrame)
+        self.assertEqual(len(img_folder.data), 0)
 
     def test_real_folder(self):
-        img = ImageFolder(path=SAMPLE_IMG_DIR)
-        data = img.to_dataframe()
-        self.assertEqual(len(data), 2)
+        img_folder = ImageFolder(directory=SAMPLE_IMG_DIR)
+        self.assertEqual(len(img_folder.data), 2)
         for key in ['ExifVersion', 'ExifImageWidth', 'ExifImageHeight']:
-            self.assertIn(key, data.columns)
+            self.assertIn(key, img_folder.data.columns)

stage6_branded_application/pycasa/ui/image_file_view.py

@@ -34,17 +34,18 @@ class ImageFileView(ModelView):
     def build_mpl_figure(self, event):
         figure = Figure()
         axes = figure.add_subplot(111)
-        axes.imshow(self.model.to_array())
+        axes.imshow(self.model.data)
         self.figure = figure
 
-    def _detect_button_fired(self):
+    @observe("detect_button")
+    def _detect_button_fired(self, event):
         self.model.detect_faces()
 
     @observe("model.faces")
     def update_mpl_figure_with_faces(self, events):
         figure = Figure()
         axes = figure.add_subplot(111)
-        axes.imshow(self.model.to_array())
+        axes.imshow(self.model.data)
 
         for face in self.model.faces:
             axes.add_patch(

stage6_branded_application/pycasa/ui/image_folder_editor.py

@@ -30,7 +30,7 @@ def create(self, parent):
     # -------------------------------------------------------------------------
 
     def _get_name(self):
-        return self.obj.path[:25]
+        return self.obj.directory[:25]
 
     def _get_tooltip(self):
-        return self.obj.path
+        return self.obj.directory