Model Difference

[yxxxxxxxx]

Hello, thank you for your implements for Part_A dataset. I notice that there are some little differences between your model(cannet.py) and the official https://github.com/weizheliu/Context-Aware-Crowd-Counting/blob/master/model.py
The official code add one convolution layer to reduce channel numbers from 1024 to 512 before sending feature maps into backend, but you input it without any other operations.
I wonder if this way works better or for some other reasons. Thank you!

[CommissarMa]

i think 1024 to 512 may not have much effect.

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---Original--- From: "yxxxxxxxx"<notifications@github.com&gt; Date: Sat, Sep 28, 2019 18:51 PM To: "CommissarMa/Context-Aware_Crowd_Counting-pytorch"<Context-Aware_Crowd_Counting-pytorch@noreply.github.com&gt;; Cc: "Subscribed"<subscribed@noreply.github.com&gt;; Subject: [CommissarMa/Context-Aware_Crowd_Counting-pytorch] Model Difference (#18) Hello, thank you for your implements for Part_A dataset. I notice that there are some little differences between your model(cannet.py) and the official https://github.com/weizheliu/Context-Aware-Crowd-Counting/blob/master/model.py The official code add one convolution layer to reduce channel numbers from 1024 to 512 before sending feature maps into backend, but you input it without any other operations. I wonder if this way works better or for some other reasons. Thank you! — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub, or mute the thread.