Reducing Resolution to 320 and anchor sizes to 8-128.

Author: datumbox

test/expect/ModelTester.test_fasterrcnn_mobilenet_v3_large_expect.pkl

@@ -372,7 +372,7 @@ def fasterrcnn_resnet50_fpn(pretrained=False, progress=True,
 
 
 def fasterrcnn_mobilenet_v3_large(pretrained=False, progress=True, num_classes=91, pretrained_backbone=True,
-                                  trainable_backbone_layers=None, min_size=320, max_size=640, **kwargs):
+                                  trainable_backbone_layers=None, min_size=320, max_size=320, **kwargs):
     """
     Constructs a Faster R-CNN model with a MobileNetV3-Large backbone. It works similarly
     to Faster R-CNN with ResNet-50 FPN backbone. See `fasterrcnn_resnet50_fpn` for more details.
@@ -402,7 +402,7 @@ def fasterrcnn_mobilenet_v3_large(pretrained=False, progress=True, num_classes=9
     backbone = mobilenet_backbone("mobilenet_v3_large", pretrained_backbone, False,
                                   trainable_layers=trainable_backbone_layers)
 
-    anchor_sizes = ((16, 32, 64, 128, 256), )
+    anchor_sizes = ((8, 16, 32, 64, 128, ), )
     aspect_ratios = ((0.5, 1.0, 2.0), )
 
     model = FasterRCNN(backbone, num_classes, rpn_anchor_generator=AnchorGenerator(anchor_sizes, aspect_ratios),
@@ -414,7 +414,7 @@ def fasterrcnn_mobilenet_v3_large(pretrained=False, progress=True, num_classes=9
 
 
 def fasterrcnn_mobilenet_v3_large_fpn(pretrained=False, progress=True, num_classes=91, pretrained_backbone=True,
-                                      trainable_backbone_layers=None, min_size=320, max_size=640, **kwargs):
+                                      trainable_backbone_layers=None, min_size=320, max_size=320, **kwargs):
     """
     Constructs a Faster R-CNN model with a MobileNetV3-Large FPN backbone. It works similarly
     to Faster R-CNN with ResNet-50 FPN backbone. See `fasterrcnn_resnet50_fpn` for more details.
@@ -444,7 +444,7 @@ def fasterrcnn_mobilenet_v3_large_fpn(pretrained=False, progress=True, num_class
     backbone = mobilenet_backbone("mobilenet_v3_large", pretrained_backbone, True,
                                   trainable_layers=trainable_backbone_layers)
 
-    anchor_sizes = ((16, 32, 64, 128, 256, ), ) * 3
+    anchor_sizes = ((8, 16, 32, 64, 128, ), ) * 3
     aspect_ratios = ((0.5, 1.0, 2.0),) * len(anchor_sizes)
 
     model = FasterRCNN(backbone, num_classes, rpn_anchor_generator=AnchorGenerator(anchor_sizes, aspect_ratios),