Commit graph

371 commits

Author SHA1 Message Date
15a3150127
DeepLabV3+: close each matplotlib figure after writing it 2022-12-15 19:14:07 +00:00
6ce121f861
DeepLabV3+: have argument for number of channels 2022-12-14 17:36:30 +00:00
1dc2ec3a46
DeepLabV3+: pathing.... again 2022-12-13 18:51:09 +00:00
eb47f8f544
dataset_mono: adjust to suit DeepLabV3+ too 2022-12-13 18:37:38 +00:00
440e693dfc
DeepLabv3+: fix pathing again 2022-12-13 18:26:00 +00:00
7e1f271bf4
deeplabv3+: fix colourmap 2022-12-13 14:02:10 +00:00
4d8ce792c9
ddeeplabv3+: fix imports/pathing errors 2022-12-13 13:38:27 +00:00
fc43f145c2
if not 2022-12-13 13:28:09 +00:00
d907dc48e5
DeepLabv3+: add logging 2022-12-13 13:20:16 +00:00
be4d928319
deeplabv3+: chmod +x 2022-12-13 13:06:42 +00:00
91846079b2
deeplabv3+ tesst: add shebang 2022-12-13 12:56:14 +00:00
8866960017
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....!)
2022-12-12 19:20:07 +00:00
4e4d42a281
LossDice: add comment 2022-12-12 18:34:20 +00:00
449bc425a7
LossDice: explicitly cast inputs to float32 2022-12-12 17:20:32 +00:00
dbf8f5617c
drop activation function in last layers 2022-12-12 17:20:04 +00:00
bcd2f1251e
LossDice: Do 1 - thing instead of -thing 2022-12-09 19:41:32 +00:00
d0dbc50bb7
debug 2022-12-09 19:33:28 +00:00
2142bb039c
again 2022-12-09 19:30:01 +00:00
7000b0f193
fixup 2022-12-09 19:23:35 +00:00
85012d0616
fixup 2022-12-09 19:18:03 +00:00
719d8e9819
strip channels layer at end 2022-12-09 19:11:00 +00:00
0129c35a35
LossDice: remove weird K.* functions 2022-12-09 19:06:26 +00:00
659fc97fd4
fix crash 2022-12-09 18:39:27 +00:00
e22c0981e6
actually use dice loss 2022-12-09 18:35:17 +00:00
649c262960
mono: switch loss from crossentropy to dice 2022-12-09 18:13:37 +00:00
7fd7c750d6
jupyter: identity test
status: FAILED, as usual....!
Don't worry though, 'cause we has a *planses*..... MUHAHAHAHAHAHAHA
* cue evil laugh *
2022-12-09 18:07:56 +00:00
cf9e8aa237
jupyter: convnext-mono identity test 2022-12-09 15:50:27 +00:00
2a1772a211
confvnext_intrevse: add shallow 2022-12-08 19:10:12 +00:00
c27869630a
I hate VSCode's git commit interface
it doesn't let you ammend
2022-12-08 18:58:54 +00:00
b3345963f3
missing arg pass 2022-12-08 18:58:32 +00:00
3dde9b69da
fixup 2022-12-08 18:56:32 +00:00
6fce39f696
WHY?!?!?! 2022-12-08 18:55:53 +00:00
26766366fc
I hate the python code intelligence
it's bad
2022-12-08 18:55:15 +00:00
ff56f591c7
I hate python 2022-12-08 18:53:37 +00:00
d37e7224f5
train-mono: tidy up arg passing 2022-12-08 18:47:03 +00:00
b53db648bf
fixup 2022-12-08 18:31:42 +00:00
18c0210704
typo 2022-12-08 17:00:25 +00:00
a3c9416cf0
LossCrossentropy: don't sum 2022-12-08 16:57:11 +00:00
08046340f4
dataset_mono: normalise heightmap 2022-12-08 16:10:34 +00:00
d997157f55
dataset_mono: log when using heightmap 2022-12-06 19:30:11 +00:00
d0f2e3d730
readfile: do transparent gzip by default
....but there's a glad to turn it off if needed
2022-12-06 19:27:39 +00:00
eac6472c97
Implement support for (optionally) taking a heightmap in 2022-12-06 18:55:58 +00:00
f92b2b3472
according to the equation it looks like it's 2 2022-12-02 17:22:46 +00:00
cad82cd1bc
CBAM: unsure if it's 1 ro 3 dense ayers in the shared mlp 2022-12-02 17:21:13 +00:00
62f6a993bb
implement CBAM, but it's UNTESTED
Convolutional Block Attention Module.
2022-12-02 17:17:45 +00:00
9d666c3b38
train mono: type=int → float 2022-12-01 15:39:44 +00:00
53dfa32685
model_mono: log learning rate 2022-12-01 15:10:51 +00:00
c384d55dff
add arg to adjust learning rate 2022-11-29 20:55:00 +00:00
8e23e9d341
model_segmenter: we're no longer using sparse 2022-11-29 19:28:27 +00:00
9a2b4c6838
dsseg: fix reshape/onehot ordering 2022-11-29 19:28:13 +00:00
df774146d9
dataset_segmenter: reshape, not squeeze 2022-11-29 19:24:54 +00:00
77b8a1a8db
dataset_segmenter: squeeze 2022-11-29 19:16:15 +00:00
01101ad30b
losscrossentropy: return the reduced value * facepalm * 2022-11-29 19:07:08 +00:00
37f196a785
LossCrossentropy: add kwargs 2022-11-29 15:40:35 +00:00
838ff56a3b
mono: fix loading checkpoint 2022-11-29 15:25:11 +00:00
dba6cbffcd
WHY. * facepalms * 2022-11-28 19:33:42 +00:00
57b8eb93fb
fixup 2022-11-28 19:09:35 +00:00
6640a41bb7
almost got it....? it's not what I expected....! 2022-11-28 19:08:50 +00:00
f48473b703
fixup 2022-11-28 19:00:11 +00:00
f6feb125e3
this iss ome serious debugging.
This commit will produce an extremely large volume of output.
2022-11-28 18:57:41 +00:00
09f81b0746
train_mono: debug
this commit will generate a large amount of debug output.
2022-11-28 16:46:17 +00:00
f39e4ade70
LayerConvNextGamma: fix config serialisation bug
.....this is unlikely to be the problem as this bug is in an unused code path.
2022-11-25 21:16:31 +00:00
e7410fb480
train_mono_predict: limit label size to 64x64
that's the size the model predicts
2022-11-25 17:47:17 +00:00
51dd484d13
fixup 2022-11-25 16:55:45 +00:00
884c4eb150
rainfall_stats: formatting again 2022-11-24 19:08:07 +00:00
bfe038086c
rainfall_stats: formatting 2022-11-24 19:07:44 +00:00
7dba03200f
fixup 2022-11-24 19:06:48 +00:00
e5258b9c66
typo 2022-11-24 19:06:13 +00:00
64d646bb13
rainfall_stats: formatting 2022-11-24 19:05:35 +00:00
675c7a7448
fixup 2022-11-24 19:03:28 +00:00
afc1cdcf02
fixup 2022-11-24 19:02:58 +00:00
e4bea89c89
typo 2022-11-24 19:01:52 +00:00
a40cbe8705
rainfall_stats: remove unused imports 2022-11-24 19:01:18 +00:00
fe57d6aab2
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.
2022-11-24 18:58:16 +00:00
3131b4f7b3
debug2 2022-11-24 18:25:32 +00:00
d55a13f536
debug 2022-11-24 18:24:03 +00:00
1f60f2a580
do_argmax 2022-11-24 18:11:03 +00:00
6c09d5254d
fixup 2022-11-24 17:57:48 +00:00
54a841efe9
train_mono_predict: convert to correct format 2022-11-24 17:56:07 +00:00
105dc5bc56
missing kwargs 2022-11-24 17:51:29 +00:00
1e1d6dd273
fixup 2022-11-24 17:48:19 +00:00
011e0aef78
update cli docs 2022-11-24 16:38:07 +00:00
773944f9fa
train_mono_predict: initial implementation 2022-11-24 16:33:50 +00:00
3a0356929c
mono: drop the sparse 2022-11-22 16:20:56 +00:00
7e8f63f8ba
fixup 2022-11-21 19:38:24 +00:00
ace4c8b246
dataset_mono: debug 2022-11-21 18:46:21 +00:00
527b34942d
convnext_inverse: kernel_size 4→2 2022-11-11 19:29:37 +00:00
0662d0854b
model_mono: fix bottleneck 2022-11-11 19:11:40 +00:00
73acda6d9a
fix debug logging 2022-11-11 19:08:38 +00:00
9da059d738
model shape logging 2022-11-11 19:03:37 +00:00
00917b2698
dataset_mono: log shapes 2022-11-11 19:02:43 +00:00
54ae88b1b4
in this entire blasted project I have yet to get the rotation of anything correct....! 2022-11-11 18:58:45 +00:00
a7a475dcd1
debug 2 2022-11-11 18:38:07 +00:00
bf2f6e9b64
debug logging
it begins again
2022-11-11 18:31:40 +00:00
481eeb3759
mono: fix dataset preprocessing
rogue dimension
2022-11-11 18:31:27 +00:00
9035450213
mono: instantiate right model 2022-11-11 18:28:29 +00:00
69a2d0cf04
fixup 2022-11-11 18:27:01 +00:00
65e801cf28
train_mono: fix crash 2022-11-11 18:26:25 +00:00
8ac5159adc
dataset_mono: simplify param passing, onehot+threshold water depth data 2022-11-11 18:23:50 +00:00
3a3f7e85da
typo 2022-11-11 18:03:09 +00:00