Remove bounding box utils and refactor retinanet #2039
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Not sure what best to do about this test failure. @sineeli do you know the minimal version of Keras we would need for all of this? |
It would require latest release |
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| @keras_hub_export("keras_hub.layers.AnchorGenerator") | ||
| class AnchorGenerator(keras.layers.Layer): | ||
| """Generates anchor boxes for object detection tasks. | ||
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these look like copy paste bugs where selecting from github removes empty newlines. bring these empty newlines back
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This is unfixed. Take a look at the diff here and restore the empty newlines.
If you copy paste from the github ui you will remove all empty newlines from the file, just something to watch out for.
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Still a few comments to address. The big one, we need to get rid of the private import of keras for that validation function. Let's remove or duplicate.
We might also want to set things up so the library still works with older keras versions, and throws an error when using an OD model that 3.8 is required. But I can help with that part.
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Oh yeah make sense, we can only import when we have Keras>=3.8.0 version and then throw error when this doesn't satisfy? I hope this works. |
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@mattdangerw what do you think on |
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| @keras_hub_export("keras_hub.layers.AnchorGenerator") | ||
| class AnchorGenerator(keras.layers.Layer): | ||
| """Generates anchor boxes for object detection tasks. | ||
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There was a problem hiding this comment.
This is unfixed. Take a look at the diff here and restore the empty newlines.
If you copy paste from the github ui you will remove all empty newlines from the file, just something to watch out for.
| @@ -40,14 +59,15 @@ def call(self, inputs): | |||
| if self.norm_std: | |||
| x = x / self._expand_non_channel_dims(self.norm_std, x) | |||
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| return x | |||
| return x, y, sample_weight | |||
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call pack_x_y_sample_weight here, it will gracefully handle the no label case.
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This still isn't done! Is there an issue with this one?
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@sineeli let me know when this is ready again. I think the torch failure looks unrelated. |
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@mattdangerw its done you can take a final look and merge it. Thanks for the review!! |
| @@ -40,14 +59,15 @@ def call(self, inputs): | |||
| if self.norm_std: | |||
| x = x / self._expand_non_channel_dims(self.norm_std, x) | |||
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| return x | |||
| return x, y, sample_weight | |||
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This still isn't done! Is there an issue with this one?
non_max_suppression,anchor_generator, andbox_matcherinto the modeling layers for better integration.