Closed marcusvlc closed 5 years ago
yes,just sum. You are right. However, when you directly use the trained model to your scene, due to the gap of different scenes, you may get terrible result. My advise is that you annotate several images of your scene and petform tranfer learning.
---Original--- From: "Marcus Vinicius"<notifications@github.com> Date: Fri, Nov 22, 2019 21:24 PM To: "CommissarMa/Context-Aware_Crowd_Counting-pytorch"<Context-Aware_Crowd_Counting-pytorch@noreply.github.com>; Cc: "Subscribed"<subscribed@noreply.github.com>; Subject: [CommissarMa/Context-Aware_Crowd_Counting-pytorch] Get result from model output (#21)
I am creating an algorithm that counts people in real time, and I am interested in using your repository, however, I have a question. When performing an inference with the command
et_dmap = model (img)
the result of the amount of people in the image would be
et_dmap.data.sum() ?
I was in doubt because I am using the .pth provided by you and I'm having a bit strange results.
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I am creating an algorithm that counts people in real time, and I am interested in using your repository, however, I have a question. When performing an inference with the command
et_dmap = model (img)
the result of the amount of people in the image would beet_dmap.data.sum() ?
I was in doubt because I am using the .pth provided by you and I'm having a bit strange results.