ageitgey / ageitgey/face_recognition
K_NN Example takes a long time for recognition
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- Dominant language
- Python
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Description
- face_recognition version: Latest
- Python version: 2.7
- Operating System: MacOSX
Description
Trying to do real-time recognition with this library to scale up to almost 4000 people.
What I Did
I've tried to run the knn example, but it seems to pretty slow and takes almost 1 second for any image. This is not ideal because I want to be able to recognize faces coming in from a webcam in real time, like the other examples.
Is this an issue with KNN or how the example was set up?
Any advice for this problem? SVMs? Simple nparrays?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by running the KNN example described in the issue on the stated Python 2.7 and MacOSX setup, using the reported nearly 1-second-per-image behavior as the baseline. Investigate whether the delay comes from KNN or the example setup, and define completion as identifying the bottleneck and determining whether real-time recognition for roughly 4,000 people is feasible.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100