Merge pull request #47 from jonathanrocher/feature/add_step_5.3

Feature: add step 5.3

Author: jonathanrocher

stage5.3_fuller_application/README.md

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+# Second real version of the pycasa ETS pyface application
+Building on the application state 5.1, this version adds a button to the folder 
+and file views so the faces can be detected.

stage5.3_fuller_application/pycasa/__init__.py

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+
+__version__ = "0.0.1"

stage5.3_fuller_application/pycasa/app/__init__.py

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+# coding=utf-8
+""" TaskApplication object for the Pycasa app.
+"""
+import logging
+
+from pyface.tasks.api import TasksApplication, TaskFactory
+from ..ui.tasks.pycasa_task import PycasaTask
+
+logger = logging.getLogger(__name__)
+
+
+class PycasaApplication(TasksApplication):
+    """ An application to say hello.
+    """
+    id = "pycasa_application"
+
+    name = "Pycasa"
+
+    description = "An example Tasks application that explores image files."
+
+    def _task_factories_default(self):
+        return [
+            TaskFactory(
+                id='pycasa.pycasa_task_factory',
+                name="Main Pycasa Task Factory",
+                factory=PycasaTask
+            )
+        ]

stage5.3_fuller_application/pycasa/app/app.py

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+
+from pycasa.app.app import PycasaApplication
+
+
+def main():
+    app = PycasaApplication()
+    app.run()
+
+
+if __name__ == '__main__':
+    main()

stage5.3_fuller_application/pycasa/app/main.py

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+from os.path import expanduser
+from traits.api import Directory, Event, HasStrictTraits
+
+
+class FileBrowser(HasStrictTraits):
+    root = Directory(expanduser("~"))
+
+    #: Item last double-clicked on in the tree view
+    requested_item = Event

stage5.3_fuller_application/pycasa/model/__init__.py

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+# General imports
+import os
+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
+
+SUPPORTED_FORMATS = [".png", ".jpg", ".jpeg"]
+
+
+class ImageFile(HasStrictTraits):
+    """ Model to hold an image file.
+    """
+    filepath = File
+
+    metadata = Property(Dict, depends_on="filepath")
+
+    data = Property(Array, depends_on="filepath")
+
+    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)
+
+    @cached_property
+    def _get_data(self):
+        return self.to_array()
+
+    @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:
+            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:
+            return {}
+
+    def detect_faces(self, scale_factor=1.2, step_ratio=1, min_size=60,
+                     max_size=600):
+        """ Detect faces in the image.
+        """
+        trained_file = data.lbp_frontal_face_cascade_filename()
+        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

stage5.3_fuller_application/pycasa/model/file_browser.py

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+# General imports
+import os
+
+import pandas as pd
+import numpy as np
+
+# ETS imports
+from traits.api import Directory, Event, HasStrictTraits, Instance
+
+# Local imports
+from .image_file import ImageFile, SUPPORTED_FORMATS
+
+FILENAME_COL = "filename"
+
+NUM_FACE_COL = "Num. faces"
+
+
+class ImageFolder(HasStrictTraits):
+    """ Model to hold an image folder.
+    """
+    path = Directory
+
+    data = Instance(pd.DataFrame)
+
+    data_updated = Event
+
+    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."
+            raise ValueError(msg)
+
+        self.data = self.to_dataframe()
+
+    def to_dataframe(self):
+        if not self.path:
+            return pd.DataFrame({FILENAME_COL: [], NUM_FACE_COL: []})
+
+        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)
+
+        return pd.DataFrame(data)
+
+    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)
+            self.data_updated = True