From 3161198a2979c7d145e86ff94c8ff0838f36ee02 Mon Sep 17 00:00:00 2001 From: Patrick Geneva Date: Mon, 14 Mar 2022 22:56:00 -0400 Subject: [PATCH] small updates --- ReadMe.md | 3 ++- docs/example_pred.png | Bin 286816 -> 175459 bytes docs/example_probs.png | Bin 63980 -> 38175 bytes 3 files changed, 2 insertions(+), 1 deletion(-) diff --git a/ReadMe.md b/ReadMe.md index 3912e45..d1d29c8 100755 --- a/ReadMe.md +++ b/ReadMe.md @@ -34,6 +34,7 @@ To find the classification for a given pixel, the argmax of the classes response ## Future Work / TODOs +- Use the larger "trainable" image set [link](https://docs.google.com/spreadsheets/d/1ZKqku0cAyWY0ELY5L2qsKYYYA2AMGbgAn4p53uoT3v8/edit#gid=0) - Allow setting of max return prop - See if dropout in network helps - Compare against baseline: https://github.com/commaai/comma10k/issues/2000 @@ -47,7 +48,7 @@ Right now there are 8908 images in the [files_trainable](https://github.com/comm It seems to perform ok after >20 epochs, but the fine detail seems to struggle. Training started at 4:53pm on March 13, 2022 and reached epoch 33 at 8:55pm (7 minutes per epoch) on a 1080Ti card. It would be interesting to perform evaluation only on "confident" network returns. - +Average loss of 0.0694 on test and 0.0549 on training data after 100 epochs Input picture (left), groundtruth (top right), and prediction (bottom right) ![](docs/example_pred.png) diff --git a/docs/example_pred.png b/docs/example_pred.png index 2141646483503d05fcec9625fe969cd083818d1b..49befab61a72dc963e866d2b43ea2cdad8b25fd1 100644 GIT binary patch literal 175459 zcmY(pcRZW#-#$$2P?TD&Rf39AMePx-6??>}O>2u0wMr3+8nt83mI`Wb(NbHYXsOz@ z(q%_m)OxPZ_j7;m`}w_I@rR3q^SI9Uv92@0*iict_$ru;jO-FzN5hni3=~C1M!rG| z0ot>+@sq(d)Da=%TdPi~t_h*JZp()O%hfwvroYlMbmli_{g`dqm}%%A5FOXU z^_x(Ir$6lAS`j7#KNKg5%zO>xYTO>*7%jL(F&%hZe{mMsU{1~>S!&_+H6(X^H6&d5 zYkFDkdg*+us&WzT+f=+SAFmI8i5VKNf2_mu;^^TtxS_T-sGU7#fNS;Lx@*#;#kY38 zAh}p4UZ2Qc1rZ0Skr5|fFMciEW9kt3?mxid$FE)s@oyVe?@-);vqFQ}8l?QW#=y6n zY711|DRdXl`&$mQC9R1&!}=_pt}b;o|UOy@g2CmY(_wK5i$m 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