An advanced facial recognition system designed for real-time identification using deep learning models and optimized vector search. Features include face detection, embedding generation, and scalable deployment options.
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Feature Request: Testing for `recognise_face()` Endpoint #11
Feature Request: Testing for recognise_face() Endpoint
Description
Once the recognise_face() endpoint is implemented, we need to create pytest tests to ensure it's working as expected. These tests should cover various scenarios, including successful face recognition, failure due to no matching face in the database, and failure due to invalid input.
Expected Behavior
The tests should confirm that the recognise_face() endpoint correctly identifies a face from a base64 string, returns the correct employee information, and handles errors appropriately.
Benefits
Testing is crucial to ensure the reliability and stability of our application. By testing the recognise_face() endpoint, we can catch any bugs or issues early and ensure that it's working as expected before it's deployed.
Tasks
[ ] Write a test to verify that the recognise_face() endpoint correctly identifies a face and returns the correct employee information.
[ ] Write a test to verify that the recognise_face() endpoint returns an appropriate error when there is no matching face in the database.
[ ] Write a test to verify that the recognise_face() endpoint returns an appropriate error when the input is invalid.
[ ] Run the tests and fix any issues that are identified.
[ ] Update the testing documentation to include the new tests.
Feature Request: Testing for
recognise_face()EndpointDescription
Once the
recognise_face()endpoint is implemented, we need to create pytest tests to ensure it's working as expected. These tests should cover various scenarios, including successful face recognition, failure due to no matching face in the database, and failure due to invalid input.Expected Behavior
The tests should confirm that the
recognise_face()endpoint correctly identifies a face from a base64 string, returns the correct employee information, and handles errors appropriately.Benefits
Testing is crucial to ensure the reliability and stability of our application. By testing the
recognise_face()endpoint, we can catch any bugs or issues early and ensure that it's working as expected before it's deployed.Tasks
recognise_face()endpoint correctly identifies a face and returns the correct employee information.recognise_face()endpoint returns an appropriate error when there is no matching face in the database.recognise_face()endpoint returns an appropriate error when the input is invalid.