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Efficientdet #256

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merged 8 commits into from
Feb 8, 2023
Merged

Efficientdet #256

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a143bb6
BoxesTo* processor is now selected via 'method' argument in the const…
Manojkumarmuru Feb 7, 2023
219b160
Processor RemoveClass now works by setting the scores at position 4+c…
Manojkumarmuru Feb 7, 2023
f58bff1
Converted to pep8 standard
Manojkumarmuru Feb 7, 2023
719438f
'class_arg' and 'method' are now passed from DetectSingleShotEfficien…
Manojkumarmuru Feb 8, 2023
fa86b69
Preprocessing and postprocessing are put under ControlMap and thereby…
Manojkumarmuru Feb 8, 2023
9485ea3
Class orders sorted based on the order they are called
Manojkumarmuru Feb 8, 2023
df370ee
EfficientDetPreprocess, EfficientDetPostprocess classes added
Manojkumarmuru Feb 8, 2023
94ad05f
Merge branch 'master' of github.com:Manojkumarmuru/paz into efficientdet
Manojkumarmuru Feb 8, 2023
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BoxesTo* processor is now selected via 'method' argument in the const… 
…ructor of ToBoxes2D class.
  • Loading branch information
@Manojkumarmuru
Manojkumarmuru committed Feb 7, 2023
commit a143bb6d3b6d322337ec8ac108abac7b4818eea7
2 changes: 1 addition & 1 deletion examples/efficientdet/detection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ def call(self, image):
ScaleBox(image_scales),
NonMaximumSuppressionPerClass(self.nms_thresh),
FilterBoxes(self.class_names, self.score_thresh),
ToBoxes2D(self.class_names, box_type='BoxesWithOneHotVectors'),
ToBoxes2D(self.class_names, method=0),
RemoveClass(self.class_names, class_arg=None)])
outputs = process_outputs(outputs)
boxes2D = postprocessing(outputs)
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23 changes: 9 additions & 14 deletions examples/efficientdet/processors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -160,28 +160,23 @@ class ToBoxes2D(Processor):
"""
def __init__(
self, class_names=None, one_hot_encoded=False,
default_score=1.0, default_class=None,
box_type='BoxesWithOneHotVectors'):
default_score=1.0, default_class=None, method=0):
if class_names is not None:
self.arg_to_class = dict(zip(range(len(class_names)), class_names))
self.one_hot_encoded = one_hot_encoded
self.default_score = default_score
self.default_class = default_class
self.box_type = box_type
method_to_processor = {0: BoxesWithOneHotVectorsToBoxes2D(
self.arg_to_class),
1: BoxesToBoxes2D(
self.default_score, self.default_class),
2: BoxesWithClassArgToBoxes2D(
self.arg_to_class, self.default_score)}
self.box_processor = method_to_processor[method]
super(ToBoxes2D, self).__init__()

def call(self, boxes):
if self.box_type == 'Boxes':
box_processor = BoxesToBoxes2D(
self.default_score, self.default_class)
elif self.box_type == 'BoxesWithOneHotVectors':
box_processor = BoxesWithOneHotVectorsToBoxes2D(self.arg_to_class)
elif self.box_type == "BoxesWithClassArg":
box_processor = BoxesWithClassArgToBoxes2D(
self.arg_to_class, self.default_score)
else:
raise ValueError('Invalid box type: ', self.box_type)
return box_processor(boxes)
return self.box_processor(boxes)


class BoxesToBoxes2D(Processor):
Expand Down