# HG changeset patch
# User iuc
# Date 1759995756 0
# Node ID e434d9b9cd13333f6f1ce1bcc88825beb45527bf
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/main/tools/biapy/ commit 66b393a7118c81d86d0fd80780d2bd551c18f3f0
diff -r 000000000000 -r e434d9b9cd13 biapy.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/biapy.xml Thu Oct 09 07:42:36 2025 +0000
@@ -0,0 +1,643 @@
+
+ Accessible deep learning on bioimages
+
+ macros.xml
+
+
+ topic_3474
+
+
+
+ operation_2945
+ operation_3925
+ operation_3443
+
+ operation_2946
+
+
+
+ operation_2944
+
+
+
+
+
+
+
+ /dev/null || true
+ #end if
+ #end if
+ #if $selected_phase in ['train_test', 'train']:
+ #if 'tcharts' in $outs
+ && mkdir -p train_charts
+ #end if
+ #if 'tlogs' in $outs
+ && mkdir -p train_logs
+ #end if
+ #end if
+ #if 'checkpoint' in $outs
+ && mkdir -p checkpoints
+ #end if
+ ]]>
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ ^[A-Za-z]+(?:-[A-Za-z]+)+$
+
+
+
+
+ ^[a-zA-Z][a-zA-Z0-9_\.]*$
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff -r 000000000000 -r e434d9b9cd13 create_yaml.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/create_yaml.py Thu Oct 09 07:42:36 2025 +0000
@@ -0,0 +1,262 @@
+import argparse
+
+import requests
+import yaml
+
+
+def download_yaml_template(workflow, dims, biapy_version=""):
+ """
+ Download a YAML template for a specific workflow and dimensions.
+
+ Parameters:
+ workflow (str): The workflow type.
+ dims (str): The dimensions (e.g., 2d, 3d).
+ biapy_version (str): The BiaPy version to use.
+
+ Returns:
+ dict: The YAML template as a dictionary.
+ """
+ template_dir_map = {
+ "SEMANTIC_SEG": "semantic_segmentation",
+ "INSTANCE_SEG": "instance_segmentation",
+ "DETECTION": "detection",
+ "DENOISING": "denoising",
+ "SUPER_RESOLUTION": "super-resolution",
+ "CLASSIFICATION": "classification",
+ "SELF_SUPERVISED": "self-supervised",
+ "IMAGE_TO_IMAGE": "image-to-image",
+ }
+ template_name = (
+ template_dir_map[workflow]
+ + "/"
+ + dims.lower() + "_" + template_dir_map[workflow] + ".yaml"
+ )
+
+ url = (
+ f"https://raw.githubusercontent.com/BiaPyX/BiaPy/"
+ f"refs/tags/v{biapy_version}/templates/{template_name}"
+ )
+ print(f"Downloading YAML template from {url}")
+ response = requests.get(url)
+ if response.status_code != 200:
+ raise RuntimeError(
+ f"Failed to download YAML template: {response.status_code}"
+ )
+ return yaml.safe_load(response.text)
+
+
+def tuple_to_list(obj):
+ """Convert tuples to lists recursively."""
+ if isinstance(obj, tuple):
+ return list(obj)
+ if isinstance(obj, dict):
+ return {k: tuple_to_list(v) for k, v in obj.items()}
+ if isinstance(obj, list):
+ return [tuple_to_list(v) for v in obj]
+ return obj
+
+
+def main():
+ parser = argparse.ArgumentParser(
+ description="Generate a YAML configuration from given arguments."
+ )
+ parser.add_argument(
+ '--input_config_path', default='', type=str,
+ help="Input configuration file to reuse"
+ )
+ parser.add_argument(
+ '--new_config', action='store_true',
+ help="Whether to create a new config or reuse an existing one."
+ )
+ parser.add_argument(
+ '--out_config_path', required=True, type=str,
+ help="Path to save the generated YAML configuration."
+ )
+ parser.add_argument(
+ '--workflow', default='semantic', type=str,
+ choices=['semantic', 'instance', 'detection', 'denoising',
+ 'sr', 'cls', 'sr2', 'i2i'],
+ )
+ parser.add_argument(
+ '--dims', default='2d', type=str,
+ choices=['2d_stack', '2d', '3d'],
+ help="Number of dimensions for the problem"
+ )
+ parser.add_argument(
+ '--obj_slices', default='', type=str,
+ choices=['', '1-5', '5-10', '10-20', '20-60', '60+'],
+ help="Number of slices for the objects in the images"
+ )
+ parser.add_argument(
+ '--obj_size', default='0-25', type=str,
+ choices=['0-25', '25-100', '100-200', '200-500', '500+'],
+ help="Size of the objects in the images"
+ )
+ parser.add_argument(
+ '--img_channel', default=1, type=int,
+ help="Number of channels in the input images"
+ )
+ parser.add_argument(
+ '--model_source', default='biapy',
+ choices=['biapy', 'bmz', 'torchvision'],
+ help="Source of the model."
+ )
+ parser.add_argument(
+ '--model', default='', type=str,
+ help=("Path to the model file if using a pre-trained model "
+ "from BiaPy or name of the model within BioImage "
+ "Model Zoo or TorchVision.")
+ )
+ parser.add_argument(
+ '--raw_train', default='', type=str,
+ help="Path to the training raw data."
+ )
+ parser.add_argument(
+ '--gt_train', default='', type=str,
+ help="Path to the training ground truth data."
+ )
+ parser.add_argument(
+ '--test_raw_path', default='', type=str,
+ help="Path to the testing raw data."
+ )
+ parser.add_argument(
+ '--test_gt_path', default='', type=str,
+ help="Path to the testing ground truth data."
+ )
+ parser.add_argument(
+ '--biapy_version', default='', type=str,
+ help="BiaPy version to use."
+ )
+
+ args = parser.parse_args()
+
+ if args.new_config:
+ workflow_map = {
+ "semantic": "SEMANTIC_SEG",
+ "instance": "INSTANCE_SEG",
+ "detection": "DETECTION",
+ "denoising": "DENOISING",
+ "sr": "SUPER_RESOLUTION",
+ "cls": "CLASSIFICATION",
+ "sr2": "SELF_SUPERVISED",
+ "i2i": "IMAGE_TO_IMAGE",
+ }
+ workflow_type = workflow_map[args.workflow]
+
+ if args.dims == "2d_stack":
+ ndim = "2D"
+ as_stack = True
+ elif args.dims == "2d":
+ ndim = "2D"
+ as_stack = True
+ elif args.dims == "3d":
+ ndim = "3D"
+ as_stack = False
+
+ config = download_yaml_template(
+ workflow_type, ndim, biapy_version=args.biapy_version
+ )
+
+ config["PROBLEM"]["TYPE"] = workflow_type
+ config["PROBLEM"]["NDIM"] = ndim
+ config["TEST"]["ANALIZE_2D_IMGS_AS_3D_STACK"] = as_stack
+
+ if args.model_source == "biapy":
+ config["MODEL"]["SOURCE"] = "biapy"
+ if args.model:
+ config["MODEL"]["LOAD_CHECKPOINT"] = True
+ config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = True
+ config.setdefault("PATHS", {})
+ config["PATHS"]["CHECKPOINT_FILE"] = args.model
+ else:
+ config["MODEL"]["LOAD_CHECKPOINT"] = False
+ config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = False
+ elif args.model_source == "bmz":
+ config["MODEL"]["SOURCE"] = "bmz"
+ config["MODEL"]["LOAD_CHECKPOINT"] = False
+ config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = False
+ config.setdefault("MODEL", {}).setdefault("BMZ", {})
+ config["MODEL"]["BMZ"]["SOURCE_MODEL_ID"] = args.model
+ elif args.model_source == "torchvision":
+ config["MODEL"]["SOURCE"] = "torchvision"
+ config["MODEL"]["LOAD_CHECKPOINT"] = False
+ config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = False
+ config["MODEL"]["TORCHVISION_MODEL_NAME"] = args.model
+
+ obj_size_map = {
+ "0-25": (256, 256),
+ "25-100": (256, 256),
+ "100-200": (512, 512),
+ "200-500": (512, 512),
+ "500+": (1024, 1024),
+ }
+ obj_size = obj_size_map[args.obj_size]
+
+ obj_slices_map = {
+ "": -1,
+ "1-5": 5,
+ "5-10": 10,
+ "10-20": 20,
+ "20-60": 40,
+ "60+": 80,
+ }
+ obj_slices = obj_slices_map[args.obj_slices]
+ if config["PROBLEM"]["NDIM"] == "2D":
+ config["DATA"]["PATCH_SIZE"] = obj_size + (args.img_channel,)
+ else:
+ assert obj_slices != -1, (
+ "For 3D problems, obj_slices must be specified."
+ )
+ config["DATA"]["PATCH_SIZE"] = (
+ (obj_slices,) + obj_size + (args.img_channel,)
+ )
+ config["DATA"]["PATCH_SIZE"] = str(config["DATA"]["PATCH_SIZE"])
+ else:
+ assert args.input_config_path, (
+ "Input configuration path must be specified when not "
+ "creating a new config."
+ )
+ with open(args.input_config_path, 'r', encoding='utf-8') as f:
+ config = yaml.safe_load(f)
+
+ if args.model:
+ config["MODEL"]["SOURCE"] = "biapy"
+ config["MODEL"]["LOAD_CHECKPOINT"] = True
+ config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = True
+ config.setdefault("PATHS", {})
+ config["PATHS"]["CHECKPOINT_FILE"] = args.model
+ else:
+ config["MODEL"]["LOAD_CHECKPOINT"] = False
+ config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = False
+
+ if args.raw_train:
+ config["TRAIN"]["ENABLE"] = True
+ config["DATA"]["TRAIN"]["PATH"] = args.raw_train
+ config["DATA"]["TRAIN"]["GT_PATH"] = args.gt_train
+ else:
+ config["TRAIN"]["ENABLE"] = False
+
+ if args.test_raw_path:
+ config["TEST"]["ENABLE"] = True
+ config["DATA"]["TEST"]["PATH"] = args.test_raw_path
+ if args.test_gt_path:
+ config["DATA"]["TEST"]["LOAD_GT"] = True
+ config["DATA"]["TEST"]["GT_PATH"] = args.test_gt_path
+ else:
+ config["DATA"]["TEST"]["LOAD_GT"] = False
+ else:
+ config["TEST"]["ENABLE"] = False
+
+ # Always use safetensors in Galaxy
+ config["MODEL"]["OUT_CHECKPOINT_FORMAT"] = "safetensors"
+
+ config = tuple_to_list(config)
+
+ with open(args.out_config_path, 'w', encoding='utf-8') as f:
+ yaml.dump(config, f, default_flow_style=False)
+
+ print(f"YAML configuration written to {args.out_config_path}")
+
+
+if __name__ == "__main__":
+ main()
diff -r 000000000000 -r e434d9b9cd13 macros.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml Thu Oct 09 07:42:36 2025 +0000
@@ -0,0 +1,73 @@
+
+ 3.6.5
+ 0
+ 25.0
+
+
+
+ python
+ biapy
+ opencv
+ openexr
+ safetensors
+
+
+
+
+
+
+
+
+
+ 10.1038/s41592-025-02699-y
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff -r 000000000000 -r e434d9b9cd13 test-data/example.yaml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/example.yaml Thu Oct 09 07:42:36 2025 +0000
@@ -0,0 +1,50 @@
+# BiaPy version: 3.6.2
+
+SYSTEM:
+ NUM_CPUS: -1
+
+PROBLEM:
+ TYPE: SEMANTIC_SEG
+ NDIM: 2D
+
+DATA:
+ PATCH_SIZE: (256, 256, 1)
+ TRAIN:
+ PATH: /path/to/data
+ GT_PATH: /path/to/data
+ IN_MEMORY: True
+ VAL:
+ SPLIT_TRAIN: 0.1
+ TEST:
+ PATH: /path/to/data
+ GT_PATH: /path/to/data
+ IN_MEMORY: True
+ LOAD_GT: True
+ PADDING: (32,32)
+
+AUGMENTOR:
+ ENABLE: True
+ AUG_SAMPLES: False
+ RANDOM_ROT: True
+ VFLIP: True
+ HFLIP: True
+
+MODEL:
+ ARCHITECTURE: unet
+ FEATURE_MAPS: [16, 32, 64, 128, 256]
+ LOAD_CHECKPOINT: False
+
+TRAIN:
+ ENABLE: False
+ OPTIMIZER: ADAMW
+ LR: 1.E-3
+ BATCH_SIZE: 6
+ EPOCHS: 20
+ PATIENCE: 20
+ LR_SCHEDULER:
+ NAME: 'onecycle' # use one-cycle learning rate scheduler
+
+TEST:
+ ENABLE: True
+ AUGMENTATION: False
+ FULL_IMG: False
diff -r 000000000000 -r e434d9b9cd13 test-data/im_0000.png
Binary file test-data/im_0000.png has changed
diff -r 000000000000 -r e434d9b9cd13 test-data/mask_0000.png
Binary file test-data/mask_0000.png has changed