SIFT memory leak
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 35/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- backend, performance
Research direction
Start by reproducing the supplied loop with af.load_image, af.vision.sift, af.device.device_gc, and af.print_mem_info, then compare its behavior with the C implementation and the ORB result described in the issue. Trace the feature cleanup around af_release_features and the SIFT/GLOH bindings; done means repeated detection no longer shows memory growth.
Written by the indexing model from the issue text.
Description
It seems that the SIFT detection leaks memory. Here is the example script I am running.
import arrayfire as af
import time
while True:
im = af.load_image('image.jpg')
feats, desc = af.vision.sift(im)
af.device.device_gc()
af.print_mem_info()
time.sleep(1)
I solved part of the leaks in #168. Apparently the features destructor wasn't called, and af_release_features needed to be called explicitly from python.
With this fix the ORB feature detection works without leaks, but SIFT and GLOH still do.
Running pretty much the same methods in C works without a memory leak. So I think there might be another destructor that ought to be called explicitly, just like af_release_features, but I could not figure out where the leak was originated from.
- Dominant language
- Python
- Stars
- 422
- Forks
- 63
- PR merge metrics
- No merged PRs in 30d
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
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- Open a pull request that references the issue number.
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