Comments (3)
Sure!
I'm still investigating another issue.
Jimp is not properly releasing the memory, so in each lambda execution, the total memory consumed is increased by 10MB.
This is the statement causing the issue:
const image = await Jimp.read(imgBuffer)
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solved it by adding
tensor.dispose();
after running the prediction
const { scores, boxes } = await predict(tfModel, tensor)
from object-detection.
Hi @jogando,
This is an amazing finding, thanks for reporting 🙏 Would you mind creating a PR to update this repository?
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Related Issues (1)
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