Image prediction with BioImage.IO model (imported from uploaded file) 3.0
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This workflows is part of the tutorial Using BioImage.IO models for image analysis in Galaxy, available in the GTN
Features
- Includes Galaxy Workflow Tests
- Includes a Galaxy Workflow Report
- Uses Galaxy Workflow Comments
Thanks to...
Workflow Author(s): Diana Chiang Jurado, Leonid Kostrykin
Tutorial Author(s): Diana Chiang Jurado, Leonid Kostrykin
Tutorial Contributor(s): Leonid Kostrykin, Saskia Hiltemann, Diana Chiang Jurado, Björn Grüning, Beatriz Serrano-Solano, Anup Kumar
Inputs
| ID | Name | Description | Type |
|---|---|---|---|
| BioImage.IO Model | BioImage.IO Model | This PyTorch [.pt] file is located in our Galaxy repository under the ML model/bioimaging-models directory. |
|
| Image for Prediction | Image for Prediction | Input image required for inference with the ML model. Ensure that the image is of the same biological type the model was trained on or is designed to process. The tool only accepts image files in TIFF or PNG format. |
|
Steps
| ID | Name | Description |
|---|---|---|
| 2 | Process image with BioImage.IO model | toolshed.g2.bx.psu.edu/repos/bgruening/bioimage_inference/bioimage_inference/2.4.1+galaxy3 |
| 3 | Split image along axes | toolshed.g2.bx.psu.edu/repos/imgteam/split_image/ip_split_image/2.2.3+galaxy1 |
| 4 | Extract dataset | __EXTRACT_DATASET__ |
| 5 | Extract dataset | __EXTRACT_DATASET__ |
| 6 | Process images using arithmetic expressions | toolshed.g2.bx.psu.edu/repos/imgteam/image_math/image_math/1.26.4+galaxy2 |
| 7 | Threshold image | toolshed.g2.bx.psu.edu/repos/imgteam/2d_auto_threshold/ip_threshold/0.18.1+galaxy3 |
| 8 | Convert binary image to label map | toolshed.g2.bx.psu.edu/repos/imgteam/binary2labelimage/ip_binary_to_labelimage/0.5+galaxy0 |
| 9 | Overlay images | toolshed.g2.bx.psu.edu/repos/imgteam/overlay_images/ip_overlay_images/0.0.4+galaxy4 |
Outputs
| ID | Name | Description | Type |
|---|---|---|---|
| out_png | out_png | n/a |
|
Version History
master
Creators and Submitter
Views: 1122 Downloads: 167 Runs: 0
Created: 2nd Jun 2025 at 10:57
AttributionsNone
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Teams: Galaxy Training Network
Organizations: Galaxy
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