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ModelZoo
ResNet50_tensorflow
Commits
6cf9a28c
Commit
6cf9a28c
authored
Nov 03, 2021
by
Scott Main
Committed by
TF Object Detection Team
Nov 03, 2021
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Add link to notebook that generates anchor box ratios with k-means clustering
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research/object_detection/g3doc/configuring_jobs.md
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6cf9a28c
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@@ -104,6 +104,13 @@ increase computation costs. Whereas generating fewer anchors that have a higher
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@@ -104,6 +104,13 @@ increase computation costs. Whereas generating fewer anchors that have a higher
chance to overlap with ground truth will both improve accuracy and reduce
chance to overlap with ground truth will both improve accuracy and reduce
computation costs.
computation costs.
And although you can manually select values for both scale and aspect ratios
that work well for your dataset, there are programmatic techniques you can use
instead. One such strategy to determine the ideal aspect ratios is to perform
k-means clustering of all the ground-truth bounding-box ratios, as shown in this
Colab notebook to
[
Generate SSD anchor box aspect ratios using k-means
clustering
](
https://colab.sandbox.google.com/github/tensorflow/models/blob/master/research/object_detection/colab_tutorials/generate_ssd_anchor_box_aspect_ratios_using_k_means_clustering.ipynb
)
.
**Single Shot Detector (SSD) full model:**
**Single Shot Detector (SSD) full model:**
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