Mercurial > repos > goeckslab > image_learner

comparison image_learner.xml @ 16:8729f69e9207 draft

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planemo upload for repository https://github.com/goeckslab/gleam.git commit bb4bcdc888d73bbfd85d78ce8999a1080fe813ff
author goeckslab
date Wed, 03 Dec 2025 01:28:52 +0000
parents d17e3a1b8659
children db9be962dc13
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15:d17e3a1b8659 16:8729f69e9207
1 <tool id="image_learner" name="Image Learner" version="0.1.4" profile="22.05"> 1 <tool id="image_learner" name="Image Learner" version="0.1.4.1" profile="22.01">
2 <description>trains and evaluates an image classification/regression model</description> 2 <description>trains and evaluates an image classification/regression model</description>
3 <requirements> 3 <requirements>
4 <container type="docker">quay.io/goeckslab/galaxy-ludwig-gpu:0.10.1</container> 4 <container type="docker">quay.io/goeckslab/galaxy-ludwig-gpu:0.10.1</container>
5 </requirements> 5 </requirements>
6 <required_files> 6 <required_files>
41 41
42 python '$__tool_directory__/image_learner_cli.py' 42 python '$__tool_directory__/image_learner_cli.py'
43 --csv-file "./${sanitized_input_csv}" 43 --csv-file "./${sanitized_input_csv}"
44 --image-zip "$image_zip" 44 --image-zip "$image_zip"
45 --model-name "$model_name" 45 --model-name "$model_name"
46 #if $use_pretrained == "true" 46 #if $scratch_fine_tune.use_pretrained == "true"
47 --use-pretrained 47 --use-pretrained
48 #if $fine_tune == "true" 48 #if $scratch_fine_tune.fine_tune == "true"
49 --fine-tune 49 --fine-tune
50 #end if 50 #end if
51 #end if 51 #end if
52 #if $advanced_settings.customize_defaults == "true" 52 #if $advanced_settings.customize_defaults == "true"
53 #if $advanced_settings.epochs 53 #if $advanced_settings.epochs
486 </assert_contents> 486 </assert_contents>
487 </element> 487 </element>
488 </output_collection> 488 </output_collection>
489 </test> 489 </test>
490 <!-- Test 7: MetaFormer with 384x384 input - verifies model correctly handles non-224x224 dimensions --> 490 <!-- Test 7: MetaFormer with 384x384 input - verifies model correctly handles non-224x224 dimensions -->
491 <test expect_num_outputs="3"> 491 <!-- <test expect_num_outputs="3">
492 <param name="input_csv" value="mnist_subset.csv" ftype="csv" /> 492 <param name="input_csv" value="mnist_subset.csv" ftype="csv" />
493 <param name="image_zip" value="mnist_subset.zip" ftype="zip" /> 493 <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
494 <param name="model_name" value="caformer_s18_384" /> 494 <param name="model_name" value="caformer_s18_384" />
495 <param name="image_resize" value="384x384" /> 495 <param name="image_resize" value="384x384" />
496 <output name="output_report"> 496 <output name="output_report">
510 <assert_contents> 510 <assert_contents>
511 <has_text text="384" /> 511 <has_text text="384" />
512 </assert_contents> 512 </assert_contents>
513 </element> 513 </element>
514 </output_collection> 514 </output_collection>
515 </test> 515 </test> -->
516 <!-- Test 8: Binary classification with custom threshold - verifies ROC curve generation for binary tasks; need to find a test dataset --> 516 <!-- Test 8: Binary classification with custom threshold - verifies ROC curve generation for binary tasks; need to find a test dataset -->
517 <!-- <test expect_num_outputs="3"> 517 <!-- <test expect_num_outputs="3">
518 <param name="input_csv" value="binary_classification.csv" ftype="csv" /> 518 <param name="input_csv" value="binary_classification.csv" ftype="csv" />
519 <param name="image_zip" value="binary_images.zip" ftype="zip" /> 519 <param name="image_zip" value="binary_images.zip" ftype="zip" />
520 <param name="model_name" value="resnet18" /> 520 <param name="model_name" value="resnet18" />