Merge pull request broadinstitute#90 from jhung0/tests

Fix Tests
toshihiroryuu · Aug 21, 2017 · 1e48b1d · 1e48b1d
2 parents c18fada + b5f5765
commit 1e48b1d
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Showing 4 changed files with 12 additions and 15 deletions.
diff --git a/keras_rcnn/backend/common.py b/keras_rcnn/backend/common.py
@@ -177,7 +177,7 @@ def overlap(a, b):
 
 
 def smooth_l1_loss(y_true, y_pred):
-    delta = 0.5
+    delta = 1
 
     x = keras.backend.abs(y_true - y_pred)
 

diff --git a/tests/layers/test_losses.py b/tests/layers/test_losses.py
@@ -1,16 +1,16 @@
 import keras.backend
 import keras_rcnn.layers
 import numpy
-
+import keras_rcnn.layers.object_detection
 
 def test_call_classification():
     anchors = 9
     layer = keras_rcnn.layers.RPNClassificationLoss(anchors=anchors)
     y_true = keras.backend.variable(100 * numpy.random.random((1, 91, 4)))
     scores = keras.backend.variable(0.5 * numpy.ones((1, 14, 14, anchors * 2)))
-    image = keras.layers.Input((224, 224, 3))
+    metadata = keras.backend.variable(numpy.array([[224, 224, 1]]))
 
-    labels, bbox_reg_targets = keras_rcnn.layers.AnchorTarget()([scores, y_true, image])
+    labels, bbox_reg_targets = keras_rcnn.layers.AnchorTarget()([scores, y_true, metadata])
     numpy.testing.assert_array_equal(layer.call([scores, labels]), scores)
 
     assert len(layer.losses) == 1
@@ -21,21 +21,20 @@ def test_call_classification():
 
 def test_call_regression():
     anchors = 9
-    image = keras.layers.Input((224, 224, 3))
-    metadata = keras.backend.int_shape(image)[1:]
+    metadata = keras.backend.variable(numpy.array([[224, 224, 1]]))
     layer = keras_rcnn.layers.RPNRegressionLoss(anchors=anchors)
     rr, cc = 14, 14
     stride = 16
     all_anchors = keras_rcnn.backend.shift((rr, cc), stride)
     # only keep anchors inside the image
-    inds_inside, y_true = keras_rcnn.backend.inside_image(all_anchors, metadata)
-    #y_true = keras.backend.variable(numpy.zeros((91, 4)))
+    inds_inside, y_true = keras_rcnn.layers.object_detection._anchor_target.inside_image(all_anchors, metadata[0])
+
     scores = keras.backend.variable(numpy.zeros((1, 14, 14, anchors * 2)))
     deltas = keras.backend.variable(numpy.zeros((1, 14, 14, anchors * 4)))
 
     expected_loss = 0
 
-    labels, bbox_reg_targets = keras_rcnn.layers.AnchorTarget()([scores, keras.backend.expand_dims(y_true, 0), image])
+    labels, bbox_reg_targets = keras_rcnn.layers.AnchorTarget()([scores, keras.backend.expand_dims(y_true, 0), metadata])
     numpy.testing.assert_array_equal(
         layer.call([deltas, bbox_reg_targets, labels]), deltas)
 

diff --git a/tests/layers/test_pooling.py b/tests/layers/test_pooling.py
@@ -23,4 +23,4 @@ def test_roi():
     a = keras.backend.placeholder(shape=(None, 224, 224, 3))
     b = keras.backend.placeholder(shape=(1, None, 4))
     y = keras_rcnn.layers.RegionOfInterest([7, 7])([a, b])
-    assert keras.backend.int_shape(y) == (1, None, 7, 7, 3)
+    assert keras.backend.int_shape(y) == (None, None, 7, 7, 3)
diff --git a/tests/test_losses.py b/tests/test_losses.py
@@ -5,12 +5,10 @@
 
 
 def test_smooth_l1_loss():
-    y_true = numpy.random.random((1, 10, 4))
-    y_pred = numpy.random.random((1, 10, 4))
+    y_true = numpy.zeros((1, 4, 4))
+    y_pred = numpy.array([[[0, 0, 0, 0], [1, 0, 0, 1], [0, 0.1, 0.5, 0.5], [0, 0, 0, 2]]])
 
     loss = keras_rcnn.backend.smooth_l1_loss(y_true, y_pred)
 
     loss = keras.backend.eval(loss)
-
-    import IPython
-    IPython.embed()
+    assert loss == 2.755