Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Efficientdet #256

Merged
merged 8 commits into from
Feb 8, 2023
Merged

Efficientdet #256

Changes from 1 commit
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
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
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
'class_arg' and 'method' are now passed from DetectSingleShotEfficien… 
…tdet pipeline
  • Loading branch information
@Manojkumarmuru
Manojkumarmuru committed Feb 8, 2023
commit 719438f9071ae75a2dc674ab7f033c8841ae72aa
9 changes: 6 additions & 3 deletions examples/efficientdet/detection.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,13 +41,16 @@ class DetectSingleShotEfficientDet(Processor):
"""
def __init__(self, model, class_names, score_thresh, nms_thresh,
mean=pr.RGB_IMAGENET_MEAN, variances=[1.0, 1.0, 1.0, 1.0],
draw=True):
class_arg=None, renormalize=False, method=0, draw=True):
self.model = model
self.class_names = class_names
self.score_thresh = score_thresh
self.nms_thresh = nms_thresh
self.variances = variances
self.draw = draw
self.class_arg = class_arg
self.renormalize = renormalize
self.method = method
self.model.prior_boxes = model.prior_boxes * model.input_shape[1]

super(DetectSingleShotEfficientDet, self).__init__()
Expand All @@ -68,11 +71,11 @@ def call(self, image):
postprocessing = SequentialProcessor([
pr.Squeeze(axis=None),
pr.DecodeBoxes(self.model.prior_boxes, variances=self.variances),
RemoveClass(class_arg=None, renormalize=False),
RemoveClass(self.class_arg, self.renormalize),
ScaleBox(image_scales),
NonMaximumSuppressionPerClass(self.nms_thresh),
FilterBoxes(self.class_names, self.score_thresh),
ToBoxes2D(self.class_names, method=0)])
ToBoxes2D(self.class_names, self.method)])
outputs = process_outputs(outputs)
boxes2D = postprocessing(outputs)
if self.draw:
Expand Down