From 9c2c123ccbc1150fc9d892ad81e646e563e2c288 Mon Sep 17 00:00:00 2001 From: Marwan Zouinkhi Date: Wed, 23 Oct 2024 12:05:46 +0200 Subject: [PATCH] better docs --- README.md | 13 +++++++++---- docs/source/_static/dacapo_diagram.png | Bin 0 -> 251004 bytes docs/source/notebooks/minimal_tutorial.py | 4 ++-- 3 files changed, 11 insertions(+), 6 deletions(-) create mode 100644 docs/source/_static/dacapo_diagram.png diff --git a/README.md b/README.md index dd37152ab..23cbcb07e 100644 --- a/README.md +++ b/README.md @@ -17,15 +17,20 @@ A framework for easy application of established machine learning techniques on large, multi-dimensional images. `dacapo` allows you to configure machine learning jobs as combinations of -[DataSplits](http://docs/api.html#datasplits), -[Architectures](http://docs/api.html#architectures), -[Tasks](http://docs/api.html#tasks), -[Trainers](http://docs/api.html#trainers), +[DataSplits](https://janelia-cellmap.github.io/dacapo/autoapi/dacapo/experiments/datasplits/index.html), +[Architectures](https://janelia-cellmap.github.io/dacapo/autoapi/dacapo/experiments/architectures/index.html), +[Tasks](https://janelia-cellmap.github.io/dacapo/autoapi/dacapo/experiments/tasks/index.html), +[Trainers](https://janelia-cellmap.github.io/dacapo/autoapi/dacapo/experiments/trainers/index.html), on arbitrarily large volumes of multi-dimensional images. `dacapo` is not tied to a particular learning framework, but currently only supports [`torch`](https://pytorch.org/) with plans to support [`tensorflow`](https://www.tensorflow.org/). + +![DaCapo Diagram](https://raw.githubusercontent.com/janelia-cellmap/dacapo/main/docs/source/_static/dacapo_diagram.png) + + + ## Installation and Setup Currently, python>=3.10 is supported. We recommend creating a new conda environment for dacapo with python 3.10. ``` diff --git a/docs/source/_static/dacapo_diagram.png b/docs/source/_static/dacapo_diagram.png new file mode 100644 index 0000000000000000000000000000000000000000..6fe04e52859e897f2e1fe8a325e8a10f8ecc478d GIT binary patch literal 251004 zcmdqIcRZVG_&6L@MYTdHZ4t9{*wl_0VyjYWl%}Dmy@^@1wPLGM+Gx>b*B&j^7*$eg z?@_T=i0${pIj5)R`=0ZAzn}NdH=ju2$^Be=-Pd&|>bfrc^vMe+K_Jj+4RzQJ5Qqu| z0#V$eIsshy{zX6*c%ybvH*p7nXc$O;WT2-R=YSR6c80e+Zs};tAe|ir5mwH3tp$A? zU4Ydfkeq^#3j%3x?ZI)^+Q!Za%C%fw&&6S91?4inrX#H5qGD}pr;c*7HbChbB2o58 zX)7)Tc@8-r832HzwFiR3$I-#bUB(B>bp%%i_)NMi#Km#6#KRuSr9?u=aZBeqhl;bC zHHWmIhyYSpSd>FjS`ZoZor{N^vl9miBI2&Irw5b^AodR~99@2ab#nhxQh>~ad=M@|B7(vsu8tO3 zA%CrN@pN-ILT-f=vUad`w081v2iA)GTI*u#?BVQg>--;}e|`NA1b}pPbbjIZS6Un$ zf1z;qQ1t@X_){SNy4u~)*Tq`shPAu1ryJ5*)e9h#o5YQajEb8z!o%6k(AnAHFI`># zi)0SbYl0#o9G7$uNINGI7ngs##~Oz4u!eGx6el1eEFdaoNK%}zjEL}6VL*Mte=OB; zwz9kD`>#tyWW=Tau@o>ID})E)|8=nyQs$nsn6(9X_EM${T9EiH+>D}WHU784M+mXs8bvPOsr 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z{!wGHjDXEGnT-~CpN3G}BPOPHzN>O4^4CD_VwDiu{Y_?Ta|X0!t2^XOS;3y|nc~A_ zDE+g*h_5s;{qT5txj}kS{I?!=jOU-j z&^fyhnudtqGA7z`_+izqq6DY(YZw0Kyo4Vp*)Dp`JM#}lxn{@9|2f^m2Vgry3ID&= zK4ZpjRiQk1lx6ep-_TCXKZoLf+W&h`=LJV({DIG8*M1g>``F3jwicyk=-dASMo7A1 literal 0 HcmV?d00001 diff --git a/docs/source/notebooks/minimal_tutorial.py b/docs/source/notebooks/minimal_tutorial.py index 58d4019cc..186fd1339 100644 --- a/docs/source/notebooks/minimal_tutorial.py +++ b/docs/source/notebooks/minimal_tutorial.py @@ -340,6 +340,8 @@ # %% import zarr +run_path = config_store.path / run_config.name + num_snapshots = run_config.num_iterations // run_config.trainer_config.snapshot_interval fig, ax = plt.subplots(num_snapshots, 3, figsize=(10, 2 * num_snapshots)) @@ -367,8 +369,6 @@ # Visualize validations import zarr -run_path = config_store.path / run_config.name - num_validations = run_config.num_iterations // run_config.validation_interval fig, ax = plt.subplots(num_validations, 4, figsize=(10, 2 * num_validations))