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d907dc48e5
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DeepLabv3+: add logging
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2022-12-13 13:20:16 +00:00 |
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be4d928319
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deeplabv3+: chmod +x
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2022-12-13 13:06:42 +00:00 |
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91846079b2
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deeplabv3+ tesst: add shebang
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2022-12-13 12:56:14 +00:00 |
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8866960017
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TEST SCRIPT: deeplabv3
ref https://keras.io/examples/vision/deeplabv3_plus/
dataset ref https://drive.google.com/uc?id=1B9A9UCJYMwTL4oBEo4RZfbMZMaZhKJaz
(the code is *terrible* spaghetti....!)
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2022-12-12 19:20:07 +00:00 |
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4e4d42a281
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LossDice: add comment
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2022-12-12 18:34:20 +00:00 |
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449bc425a7
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LossDice: explicitly cast inputs to float32
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2022-12-12 17:20:32 +00:00 |
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dbf8f5617c
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drop activation function in last layers
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2022-12-12 17:20:04 +00:00 |
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bcd2f1251e
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LossDice: Do 1 - thing instead of -thing
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2022-12-09 19:41:32 +00:00 |
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d0dbc50bb7
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debug
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2022-12-09 19:33:28 +00:00 |
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2142bb039c
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again
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2022-12-09 19:30:01 +00:00 |
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7000b0f193
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fixup
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2022-12-09 19:23:35 +00:00 |
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85012d0616
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fixup
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2022-12-09 19:18:03 +00:00 |
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719d8e9819
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strip channels layer at end
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2022-12-09 19:11:00 +00:00 |
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0129c35a35
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LossDice: remove weird K.* functions
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2022-12-09 19:06:26 +00:00 |
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659fc97fd4
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fix crash
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2022-12-09 18:39:27 +00:00 |
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e22c0981e6
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actually use dice loss
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2022-12-09 18:35:17 +00:00 |
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649c262960
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mono: switch loss from crossentropy to dice
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2022-12-09 18:13:37 +00:00 |
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7fd7c750d6
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jupyter: identity test
status: FAILED, as usual....!
Don't worry though, 'cause we has a *planses*..... MUHAHAHAHAHAHAHA
* cue evil laugh *
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2022-12-09 18:07:56 +00:00 |
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cf9e8aa237
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jupyter: convnext-mono identity test
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2022-12-09 15:50:27 +00:00 |
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2a1772a211
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confvnext_intrevse: add shallow
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2022-12-08 19:10:12 +00:00 |
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c27869630a
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I hate VSCode's git commit interface
it doesn't let you ammend
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2022-12-08 18:58:54 +00:00 |
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b3345963f3
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missing arg pass
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2022-12-08 18:58:32 +00:00 |
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3dde9b69da
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fixup
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2022-12-08 18:56:32 +00:00 |
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6fce39f696
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WHY?!?!?!
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2022-12-08 18:55:53 +00:00 |
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26766366fc
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I hate the python code intelligence
it's bad
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2022-12-08 18:55:15 +00:00 |
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ff56f591c7
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I hate python
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2022-12-08 18:53:37 +00:00 |
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d37e7224f5
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train-mono: tidy up arg passing
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2022-12-08 18:47:03 +00:00 |
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b53db648bf
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fixup
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2022-12-08 18:31:42 +00:00 |
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18c0210704
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typo
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2022-12-08 17:00:25 +00:00 |
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a3c9416cf0
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LossCrossentropy: don't sum
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2022-12-08 16:57:11 +00:00 |
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08046340f4
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dataset_mono: normalise heightmap
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2022-12-08 16:10:34 +00:00 |
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d997157f55
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dataset_mono: log when using heightmap
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2022-12-06 19:30:11 +00:00 |
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d0f2e3d730
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readfile: do transparent gzip by default
....but there's a glad to turn it off if needed
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2022-12-06 19:27:39 +00:00 |
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eac6472c97
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Implement support for (optionally) taking a heightmap in
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2022-12-06 18:55:58 +00:00 |
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f92b2b3472
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according to the equation it looks like it's 2
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2022-12-02 17:22:46 +00:00 |
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cad82cd1bc
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CBAM: unsure if it's 1 ro 3 dense ayers in the shared mlp
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2022-12-02 17:21:13 +00:00 |
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62f6a993bb
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implement CBAM, but it's UNTESTED
Convolutional Block Attention Module.
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2022-12-02 17:17:45 +00:00 |
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9d666c3b38
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train mono: type=int → float
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2022-12-01 15:39:44 +00:00 |
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53dfa32685
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model_mono: log learning rate
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2022-12-01 15:10:51 +00:00 |
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c384d55dff
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add arg to adjust learning rate
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2022-11-29 20:55:00 +00:00 |
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8e23e9d341
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model_segmenter: we're no longer using sparse
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2022-11-29 19:28:27 +00:00 |
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9a2b4c6838
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dsseg: fix reshape/onehot ordering
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2022-11-29 19:28:13 +00:00 |
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df774146d9
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dataset_segmenter: reshape, not squeeze
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2022-11-29 19:24:54 +00:00 |
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77b8a1a8db
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dataset_segmenter: squeeze
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2022-11-29 19:16:15 +00:00 |
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01101ad30b
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losscrossentropy: return the reduced value * facepalm *
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2022-11-29 19:07:08 +00:00 |
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37f196a785
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LossCrossentropy: add kwargs
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2022-11-29 15:40:35 +00:00 |
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838ff56a3b
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mono: fix loading checkpoint
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2022-11-29 15:25:11 +00:00 |
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dba6cbffcd
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WHY. * facepalms *
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2022-11-28 19:33:42 +00:00 |
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57b8eb93fb
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fixup
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2022-11-28 19:09:35 +00:00 |
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6640a41bb7
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almost got it....? it's not what I expected....!
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2022-11-28 19:08:50 +00:00 |
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f48473b703
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fixup
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2022-11-28 19:00:11 +00:00 |
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f6feb125e3
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this iss ome serious debugging.
This commit will produce an extremely large volume of output.
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2022-11-28 18:57:41 +00:00 |
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09f81b0746
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train_mono: debug
this commit will generate a large amount of debug output.
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2022-11-28 16:46:17 +00:00 |
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f39e4ade70
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LayerConvNextGamma: fix config serialisation bug
.....this is unlikely to be the problem as this bug is in an unused code path.
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2022-11-25 21:16:31 +00:00 |
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e7410fb480
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train_mono_predict: limit label size to 64x64
that's the size the model predicts
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2022-11-25 17:47:17 +00:00 |
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51dd484d13
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fixup
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2022-11-25 16:55:45 +00:00 |
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884c4eb150
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rainfall_stats: formatting again
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2022-11-24 19:08:07 +00:00 |
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bfe038086c
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rainfall_stats: formatting
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2022-11-24 19:07:44 +00:00 |
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7dba03200f
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fixup
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2022-11-24 19:06:48 +00:00 |
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e5258b9c66
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typo
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2022-11-24 19:06:13 +00:00 |
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64d646bb13
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rainfall_stats: formatting
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2022-11-24 19:05:35 +00:00 |
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675c7a7448
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fixup
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2022-11-24 19:03:28 +00:00 |
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afc1cdcf02
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fixup
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2022-11-24 19:02:58 +00:00 |
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e4bea89c89
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typo
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2022-11-24 19:01:52 +00:00 |
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a40cbe8705
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rainfall_stats: remove unused imports
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2022-11-24 19:01:18 +00:00 |
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fe57d6aab2
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rainfall_stats: initial implementation
this might reveal why we are having problems. If most/all the rainfall radar
data is v small numbers, normalising
might help.
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2022-11-24 18:58:16 +00:00 |
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3131b4f7b3
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debug2
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2022-11-24 18:25:32 +00:00 |
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d55a13f536
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debug
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2022-11-24 18:24:03 +00:00 |
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1f60f2a580
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do_argmax
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2022-11-24 18:11:03 +00:00 |
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6c09d5254d
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fixup
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2022-11-24 17:57:48 +00:00 |
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54a841efe9
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train_mono_predict: convert to correct format
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2022-11-24 17:56:07 +00:00 |
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105dc5bc56
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missing kwargs
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2022-11-24 17:51:29 +00:00 |
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1e1d6dd273
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fixup
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2022-11-24 17:48:19 +00:00 |
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011e0aef78
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update cli docs
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2022-11-24 16:38:07 +00:00 |
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773944f9fa
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train_mono_predict: initial implementation
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2022-11-24 16:33:50 +00:00 |
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3a0356929c
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mono: drop the sparse
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2022-11-22 16:20:56 +00:00 |
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7e8f63f8ba
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fixup
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2022-11-21 19:38:24 +00:00 |
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ace4c8b246
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dataset_mono: debug
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2022-11-21 18:46:21 +00:00 |
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527b34942d
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convnext_inverse: kernel_size 4→2
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2022-11-11 19:29:37 +00:00 |
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0662d0854b
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model_mono: fix bottleneck
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2022-11-11 19:11:40 +00:00 |
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73acda6d9a
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fix debug logging
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2022-11-11 19:08:38 +00:00 |
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9da059d738
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model shape logging
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2022-11-11 19:03:37 +00:00 |
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00917b2698
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dataset_mono: log shapes
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2022-11-11 19:02:43 +00:00 |
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54ae88b1b4
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in this entire blasted project I have yet to get the rotation of anything correct....!
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2022-11-11 18:58:45 +00:00 |
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a7a475dcd1
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debug 2
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2022-11-11 18:38:07 +00:00 |
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bf2f6e9b64
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debug logging
it begins again
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2022-11-11 18:31:40 +00:00 |
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481eeb3759
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mono: fix dataset preprocessing
rogue dimension
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2022-11-11 18:31:27 +00:00 |
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9035450213
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mono: instantiate right model
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2022-11-11 18:28:29 +00:00 |
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69a2d0cf04
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fixup
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2022-11-11 18:27:01 +00:00 |
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65e801cf28
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train_mono: fix crash
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2022-11-11 18:26:25 +00:00 |
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8ac5159adc
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dataset_mono: simplify param passing, onehot+threshold water depth data
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2022-11-11 18:23:50 +00:00 |
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3a3f7e85da
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typo
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2022-11-11 18:03:09 +00:00 |
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3313f77c88
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Add (untested) mono rainfall → water depth model
* sighs *
Unfortunately I can't seem to get contrastive learning to work.....
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2022-11-10 22:36:11 +00:00 |
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9384b89165
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model_segmentation: spare → normal crossentropy, activation functions at end
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2022-11-10 20:53:37 +00:00 |
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b6676e7361
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switch from sparse to normal crossentropy
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2022-11-10 20:50:56 +00:00 |
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d8be26d476
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Merge branch 'main' of git.starbeamrainbowlabs.com:sbrl/PhD-Rainfall-Radar
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2022-11-10 20:49:01 +00:00 |
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b03388de60
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dataset_segmenter: DEBUG: fix water shape
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2022-11-10 20:48:21 +00:00 |
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daf691bf43
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typo
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2022-11-10 19:55:00 +00:00 |
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0aa2ce19f5
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read_metadata: support file inputs as well as dirs
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2022-11-10 19:53:30 +00:00 |
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aa7d9b8cf6
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fixup
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2022-11-10 19:46:09 +00:00 |
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