Make padding optional in object detection data extension

This change makes it optional to pad images when creating an object detection dataset.

A form validator is added to verify that either both or none of width/height are specified when validating the form.
Doing this in the form validator instead of (like formerly) the extension instanciation helps drop a more user-friendly error.

Template updated to show width/height on same row.

digits/extensions/data/objectDetection/data.py

@@ -15,7 +15,7 @@
 from ..interface import DataIngestionInterface
 from .forms import DatasetForm
 from .utils import GroundTruth, GroundTruthObj
-from .utils import bbox_to_array, resize_bbox_list
+from .utils import bbox_to_array, pad_image, resize_bbox_list
 
 TEMPLATE = "template.html"
 
@@ -41,12 +41,6 @@ def __init__(self, **kwargs):
         else:
             self.class_mappings = None
 
-        if ((self.val_image_folder == '') ^ (self.val_label_folder == '')):
-            raise ValueError("You must specify either both val_image_folder and val_label_folder or none")
-
-        if ((self.resize_image_width is None) ^ (self.resize_image_height is None)):
-            raise ValueError("You must specify either both resize_image_width and resize_image_height or none")
-
         # this will be set when we know the phase we are encoding
         self.ground_truth = None
 
@@ -59,20 +53,26 @@ def encode_entry(self, entry):
 
         # (1) image part
 
-        # load from file
+        # load from file (this returns a PIL image)
         img = digits.utils.image.load_image(image_filename)
         if self.channel_conversion != 'none':
             if img.mode != self.channel_conversion:
                 # convert to different image mode if necessary
                 img = img.convert(self.channel_conversion)
 
-        # pad
-        img = self.pad_image(img)
+        # note: the form validator ensured that either none
+        # or both width/height were specified
+        if self.padding_image_width:
+            # pad image
+            img = pad_image(
+                img,
+                self.padding_image_height,
+                self.padding_image_width)
 
         if self.resize_image_width is not None:
-            # resize
-            resize_ratio_x = float(self.resize_image_width) / self.padding_image_width
-            resize_ratio_y = float(self.resize_image_height) / self.padding_image_height
+            resize_ratio_x = float(self.resize_image_width) / img.size[0]
+            resize_ratio_y = float(self.resize_image_height) / img.size[1]
+            # resize and convert to numpy HWC
             img = digits.utils.image.resize_image(
                 img,
                 self.resize_image_height,
@@ -234,25 +234,3 @@ def make_image_list(self, folder):
         # shuffle
         random.shuffle(image_files)
         return image_files
-
-    def pad_image(self, img):
-        """
-        pad a single image to the dimensions specified in form
-        """
-        src_width = img.size[0]
-        src_height = img.size[1]
-
-        if self.padding_image_width < src_width:
-            raise ValueError("Source image width %d is greater than padding width %d" % (src_width, self.padding_image_width))
-
-        if self.padding_image_height < src_height:
-            raise ValueError("Source image height %d is greater than padding height %d" % (src_height, self.padding_image_height))
-
-        padded_img = PIL.Image.new(
-            img.mode,
-            (self.padding_image_width, self.padding_image_height),
-            "black")
-
-        padded_img.paste(img, (0, 0))  # copy to top-left corner
-
-        return padded_img

digits/extensions/data/objectDetection/forms.py

@@ -7,7 +7,7 @@
 
 from digits import utils
 from digits.utils import subclass
-
+from digits.utils.forms import validate_required_if_set
 
 @subclass
 class DatasetForm(Form):
@@ -46,7 +46,7 @@ def validate_folder_path(form, field):
     val_image_folder = utils.forms.StringField(
         u'Validation image folder',
         validators=[
-            validators.Optional(),
+            validate_required_if_set('val_label_folder'),
             validate_folder_path,
             ],
         tooltip="Indicate a folder of images to use for training"
@@ -55,7 +55,7 @@ def validate_folder_path(form, field):
     val_label_folder = utils.forms.StringField(
         u'Validation label folder',
         validators=[
-            validators.Optional(),
+            validate_required_if_set('val_image_folder'),
             validate_folder_path,
             ],
         tooltip="Indicate a folder of validation labels"
@@ -64,7 +64,7 @@ def validate_folder_path(form, field):
     resize_image_width = utils.forms.IntegerField(
         u'Resize Image Width',
         validators=[
-            validators.Optional(),
+            validate_required_if_set('resize_image_height'),
             validators.NumberRange(min=1),
             ],
         tooltip="If specified, images will be resized to that dimension after padding"
@@ -73,7 +73,7 @@ def validate_folder_path(form, field):
     resize_image_height = utils.forms.IntegerField(
         u'Resize Image Height',
         validators=[
-            validators.Optional(),
+            validate_required_if_set('resize_image_width'),
             validators.NumberRange(min=1),
             ],
         tooltip="If specified, images will be resized to that dimension after padding"
@@ -83,20 +83,20 @@ def validate_folder_path(form, field):
         u'Padding Image Width',
         default=1248,
         validators=[
-            validators.DataRequired(),
+            validate_required_if_set('padding_image_height'),
             validators.NumberRange(min=1),
             ],
-        tooltip="Images will be padded to that dimension"
+        tooltip="If specified, images will be padded to that dimension"
         )
 
     padding_image_height = utils.forms.IntegerField(
         u'Padding Image Height',
         default=384,
         validators=[
-            validators.DataRequired(),
+            validate_required_if_set('padding_image_width'),
             validators.NumberRange(min=1),
             ],
-        tooltip="Images will be padded to that dimension"
+        tooltip="If specified, images will be padded to that dimension"
         )
 
     channel_conversion = utils.forms.SelectField(

digits/extensions/data/objectDetection/template.html

@@ -39,28 +39,32 @@ <h3>Object Detection Dataset Options</h3>
     {{ form.val_label_folder(class='form-control autocomplete_path', placeholder='folder')}}
 </div>
 
-<div class="form-group{{mark_errors([form.padding_image_width])}}">
-    {{ form.padding_image_width.label }}
-    {{ form.padding_image_width.tooltip }}
-    {{ form.padding_image_width(class='form-control')}}
+<div class="form-group{{mark_errors([form.padding_image_width, form.padding_image_height])}}">
+    <label>Pad image (Width x Height)</label>
+    <span name="pad_dims_explanation"
+          class="explanation-tooltip glyphicon glyphicon-question-sign"
+          data-container="body"
+          title="If specified, input images will be padded to that dimension. Pad dimensions should be greater than those of input images."
+          ></span>
+    <div class="input-group">
+        {{ form.padding_image_width(size=4, placeholder='width', class='form-control') }}
+        <span class="input-group-addon">x</span>
+        {{ form.padding_image_height(size=4, placeholder='height', class='form-control') }}
+    </div>
 </div>
 
-<div class="form-group{{mark_errors([form.padding_image_height])}}">
-    {{ form.padding_image_height.label }}
-    {{ form.padding_image_height.tooltip }}
-    {{ form.padding_image_height(class='form-control')}}
-</div>
-
-<div class="form-group{{mark_errors([form.resize_image_width])}}">
-    {{ form.resize_image_width.label }}
-    {{ form.resize_image_width.tooltip }}
-    {{ form.resize_image_width(class='form-control')}}
-</div>
-
-<div class="form-group{{mark_errors([form.resize_image_height])}}">
-    {{ form.resize_image_height.label }}
-    {{ form.resize_image_height.tooltip }}
-    {{ form.resize_image_height(class='form-control')}}
+<div class="form-group{{mark_errors([form.resize_image_width, form.resize_image_height])}}">
+    <label>Resize image (Width x Height)</label>
+    <span name="resize_dims_explanation"
+          class="explanation-tooltip glyphicon glyphicon-question-sign"
+          data-container="body"
+          title="If specified, input images will be squashed to that dimension after padding."
+          ></span>
+    <div class="input-group">
+        {{ form.resize_image_width(size=4, placeholder='width', class='form-control') }}
+        <span class="input-group-addon">x</span>
+        {{ form.resize_image_height(size=4, placeholder='height', class='form-control') }}
+    </div>
 </div>
 
 <div class="form-group{{mark_errors([form.channel_conversion])}}">

digits/extensions/data/objectDetection/utils.py

@@ -1,9 +1,11 @@
 # Copyright (c) 2016, NVIDIA CORPORATION.  All rights reserved.
 
 import csv
-import numpy as np
 import os
 
+import numpy as np
+import PIL.Image
+
 class ObjectType:
 
     Dontcare, Car, Van, Truck, Bus, Pickup, VehicleWithTrailer, SpecialVehicle,\
@@ -268,6 +270,29 @@ def bbox_overlap(abox, bbox):
 
     return overlap_pix, overlap_box
 
+
+def pad_image(img, padding_image_height, padding_image_width):
+    """
+    pad a single image to the specified dimensions
+    """
+    src_width = img.size[0]
+    src_height = img.size[1]
+
+    if padding_image_width < src_width:
+        raise ValueError("Source image width %d is greater than padding width %d" % (src_width, padding_image_width))
+
+    if padding_image_height < src_height:
+        raise ValueError("Source image height %d is greater than padding height %d" % (src_height, padding_image_height))
+
+    padded_img = PIL.Image.new(
+        img.mode,
+        (padding_image_width, padding_image_height),
+        "black")
+    padded_img.paste(img, (0, 0))  # copy to top-left corner
+
+    return padded_img
+
+
 def resize_bbox_list(bboxlist, rescale_x=1, rescale_y=1):
         # this is expecting x1,y1,w,h:
         bboxListNew = []

digits/utils/forms.py

@@ -38,6 +38,31 @@ def _validator(form, field):
 
     return _validator
 
+def validate_required_if_set(other_field, **kwargs):
+    """
+    Used as a validator within a wtforms.Form
+
+    This implements a conditional DataRequired
+    `other_field` is a field name; if set, the other field makes it mandatory
+    to set the field being tested
+    """
+    def _validator(form, field):
+        other_field_value = getattr(form, other_field).data
+        if other_field_value is not None and other_field_value is not "":
+            # Verify that data exists
+            if field.data is None \
+                    or (isinstance(field.data, (str, unicode))
+                            and not field.data.strip()) \
+                    or (isinstance(field.data, FileStorage)
+                            and not field.data.filename.strip()):
+                raise validators.ValidationError('This field is required if %s is set.' % other_field)
+        else:
+            # This field is not required, ignore other errors
+            field.errors[:] = []
+            raise validators.StopValidation()
+
+    return _validator
+
 def validate_greater_than(fieldname):
     """
     Compares the value of two fields the value of self is to be greater than the supplied field.