comparison image_learner.xml @ 12:bcfa2e234a80 draft

planemo upload for repository https://github.com/goeckslab/gleam.git commit 96bab8325992d16fcaad8e0a4dc4c62b00e2abc2

11:c5150cceab47

    <tests>
        <test expect_num_outputs="3">
            <param name="input_csv" value="mnist_subset.csv" ftype="csv" />
            <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
            <param name="model_name" value="resnet18" />
            <output name="output_report">
                <assert_contents>
                    <has_text text="Results Summary" />
                    <has_text text="Train/Validation Results" />
                    <has_text text="Test Results" />
                </assert_contents>
            </output>

            <output_collection name="output_pred_csv" type="list" >
                <element name="predictions.csv" >
                    <assert_contents>
                        <has_n_columns n="1" />
                    </assert_contents>
                </element>
            </output_collection>
        </test>
         <test expect_num_outputs="3">
            <param name="input_csv" value="mnist_subset.csv" ftype="csv" />
            <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
            <param name="model_name" value="vit_b_16" />
            <output name="output_report">
                <assert_contents>
                    <has_text text="Results Summary" />
                    <has_text text="Train/Validation Results" />
                    <has_text text="Test Results" />
                </assert_contents>
            </output>

            <output_collection name="output_pred_csv" type="list" >
                <element name="predictions.csv" >
                    <assert_contents>
                        <has_n_columns n="1" />
                    </assert_contents>
                </element>
            </output_collection>
        </test>
        <test expect_num_outputs="3">
            <param name="input_csv" value="mnist_subset.csv" ftype="csv" />
            <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
            <param name="model_name" value="resnet18" />
            <param name="augmentation" value="random_horizontal_flip,random_vertical_flip,random_rotate" />
            <output name="output_report">
                <assert_contents>
                    <has_text text="Results Summary" />
                    <has_text text="Train/Validation Results" />

                    </assert_contents>
                </element>
            </output_collection>
        </test> -->
        <!-- Test 9: PoolFormerV2 model configuration - verifies custom_model parameter persists in config -->
        <test expect_num_outputs="3">
            <param name="input_csv" value="mnist_subset.csv" ftype="csv" />
            <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
            <param name="model_name" value="poolformerv2_s12" />
            <output name="output_report">
                <assert_contents>
                    <has_text text="Results Summary" />
                    <has_text text="Train/Validation Results" />
                    <has_text text="Test Results" />
                </assert_contents>
            </output>
            <output_collection name="output_pred_csv" type="list" >
                <element name="predictions.csv" >
                    <assert_contents>
                        <has_n_columns n="1" />
                    </assert_contents>
                </element>
            </output_collection>
        </test>
        <!-- Test 10: Multi-class classification with ROC curves - verifies robust ROC-AUC plot generation -->
        <!-- <test expect_num_outputs="3">
            <param name="input_csv" value="mnist_subset.csv" ftype="csv" />
            <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
            <param name="model_name" value="resnet18" />

                        <has_n_columns n="1" />
                    </assert_contents>
                </element>
            </output_collection>
        </test> -->
    </tests>
    <help>
        <![CDATA[
**What it does**
Image Learner for Classification/regression: trains and evaluates a image classification/regression model.

12:bcfa2e234a80

    <tests>
        <test expect_num_outputs="3">
            <param name="input_csv" value="mnist_subset.csv" ftype="csv" />
            <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
            <param name="model_name" value="resnet18" />
            <param name="augmentation" value="random_horizontal_flip,random_vertical_flip,random_rotate" />
            <output name="output_report">
                <assert_contents>
                    <has_text text="Results Summary" />
                    <has_text text="Train/Validation Results" />

                    </assert_contents>
                </element>
            </output_collection>
        </test> -->
        <!-- Test 9: PoolFormerV2 model configuration - verifies custom_model parameter persists in config -->
        <!-- Test 10: Multi-class classification with ROC curves - verifies robust ROC-AUC plot generation -->
        <!-- <test expect_num_outputs="3">
            <param name="input_csv" value="mnist_subset.csv" ftype="csv" />
            <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
            <param name="model_name" value="resnet18" />

                        <has_n_columns n="1" />
                    </assert_contents>
                </element>
            </output_collection>
        </test> -->
        <test expect_num_outputs="3">
            <param name="input_csv" value="mnist_subset_binary.csv" ftype="csv" />
            <param name="image_zip" value="mnist_subset.zip" ftype="zip" />
            <param name="model_name" value="resnet18" />
            <param name="customize_defaults" value="true" />
            <param name="threshold" value="0.6" />
            <output name="output_report">
                <assert_contents>
                    <has_text text="Accuracy" />
                    <has_text text="Precision" />
                    <has_text text="Learning Curves Label Accuracy" />
                </assert_contents>
            </output>
            <output_collection name="output_pred_csv" type="list" >
                <element name="predictions.csv" >
                    <assert_contents>
                        <has_n_columns n="1" />
                    </assert_contents>
                </element>
            </output_collection>
        </test>
    </tests>
    <help>
        <![CDATA[
**What it does**
Image Learner for Classification/regression: trains and evaluates a image classification/regression model.