Added Confidence Argument to keypoint detection model #354
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SolomonLake
requested changes
Jun 4, 2025
SolomonLake
requested changes
Jun 10, 2025
| instance = KeypointDetectionModel(self.api_key, self.version_id, version=self.version) | ||
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| self.assertEqual(instance.id, self.version_id) | ||
| self.assertEqual(instance.api_key, self.api_key) |
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KeypointDetectionModel doesn't have api_key on instance, and there are several other errors here -- can you run python -m unittest and make sure tests are passing?
| @@ -26,6 +26,7 @@ def __init__( | |||
| id: str, | |||
| name: Optional[str] = None, | |||
| version: Optional[str] = None, | |||
| confidence: Optional[int] = 10, | |||
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let's default to 40, that's the standard in this repo
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| responses.add(responses.POST, self.api_url, json=MOCK_RESPONSE, status=200) | ||
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| result = instance.predict("tests/images/MM2A_46_R_T.jpg", confidence=30) |
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if you want to be able to pass confidence into .predict (which is a good idea), you will need to add it to predict arguments.
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Description
A new "Confidence" argument has been added to the keypoint detection model (based on the confidence argument found in the object detection model)
Type of change
Please delete options that are not relevant.
How has this change been tested, please provide a testcase or example of how you tested the change?
A Dedicated keypoint detection model test file has been made with multiple test cases including one where the confidence is changed
Any specific deployment considerations
Docs