fix: allow model.predict to handle numpy array inputs #350
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Description
This PR adds support for numpy array inputs to the model.predict function, fixing issue #346. Previously, model.predict would fail when trying to process numpy array inputs in segmentation models, despite working with file paths. This change enables consistent behavior across all input types.
Type of change
How has this change been tested, please provide a testcase or example of how you tested the change?
Added comprehensive unit tests in test_instance_segmentation.py:
Example test case:
image_array = np.zeros((100, 100, 3), dtype=np.uint8)
image_array[30:70, 30:70] = 255
result = model.predict(image_array)
Docs