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comparison create_yaml.py @ 0:e434d9b9cd13 draft default tip

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/main/tools/biapy/ commit 66b393a7118c81d86d0fd80780d2bd551c18f3f0
author iuc
date Thu, 09 Oct 2025 07:42:36 +0000
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-1:000000000000 0:e434d9b9cd13
1 import argparse
2
3 import requests
4 import yaml
5
6
7 def download_yaml_template(workflow, dims, biapy_version=""):
8 """
9 Download a YAML template for a specific workflow and dimensions.
10
11 Parameters:
12 workflow (str): The workflow type.
13 dims (str): The dimensions (e.g., 2d, 3d).
14 biapy_version (str): The BiaPy version to use.
15
16 Returns:
17 dict: The YAML template as a dictionary.
18 """
19 template_dir_map = {
20 "SEMANTIC_SEG": "semantic_segmentation",
21 "INSTANCE_SEG": "instance_segmentation",
22 "DETECTION": "detection",
23 "DENOISING": "denoising",
24 "SUPER_RESOLUTION": "super-resolution",
25 "CLASSIFICATION": "classification",
26 "SELF_SUPERVISED": "self-supervised",
27 "IMAGE_TO_IMAGE": "image-to-image",
28 }
29 template_name = (
30 template_dir_map[workflow]
31 + "/"
32 + dims.lower() + "_" + template_dir_map[workflow] + ".yaml"
33 )
34
35 url = (
36 f"https://raw.githubusercontent.com/BiaPyX/BiaPy/"
37 f"refs/tags/v{biapy_version}/templates/{template_name}"
38 )
39 print(f"Downloading YAML template from {url}")
40 response = requests.get(url)
41 if response.status_code != 200:
42 raise RuntimeError(
43 f"Failed to download YAML template: {response.status_code}"
44 )
45 return yaml.safe_load(response.text)
46
47
48 def tuple_to_list(obj):
49 """Convert tuples to lists recursively."""
50 if isinstance(obj, tuple):
51 return list(obj)
52 if isinstance(obj, dict):
53 return {k: tuple_to_list(v) for k, v in obj.items()}
54 if isinstance(obj, list):
55 return [tuple_to_list(v) for v in obj]
56 return obj
57
58
59 def main():
60 parser = argparse.ArgumentParser(
61 description="Generate a YAML configuration from given arguments."
62 )
63 parser.add_argument(
64 '--input_config_path', default='', type=str,
65 help="Input configuration file to reuse"
66 )
67 parser.add_argument(
68 '--new_config', action='store_true',
69 help="Whether to create a new config or reuse an existing one."
70 )
71 parser.add_argument(
72 '--out_config_path', required=True, type=str,
73 help="Path to save the generated YAML configuration."
74 )
75 parser.add_argument(
76 '--workflow', default='semantic', type=str,
77 choices=['semantic', 'instance', 'detection', 'denoising',
78 'sr', 'cls', 'sr2', 'i2i'],
79 )
80 parser.add_argument(
81 '--dims', default='2d', type=str,
82 choices=['2d_stack', '2d', '3d'],
83 help="Number of dimensions for the problem"
84 )
85 parser.add_argument(
86 '--obj_slices', default='', type=str,
87 choices=['', '1-5', '5-10', '10-20', '20-60', '60+'],
88 help="Number of slices for the objects in the images"
89 )
90 parser.add_argument(
91 '--obj_size', default='0-25', type=str,
92 choices=['0-25', '25-100', '100-200', '200-500', '500+'],
93 help="Size of the objects in the images"
94 )
95 parser.add_argument(
96 '--img_channel', default=1, type=int,
97 help="Number of channels in the input images"
98 )
99 parser.add_argument(
100 '--model_source', default='biapy',
101 choices=['biapy', 'bmz', 'torchvision'],
102 help="Source of the model."
103 )
104 parser.add_argument(
105 '--model', default='', type=str,
106 help=("Path to the model file if using a pre-trained model "
107 "from BiaPy or name of the model within BioImage "
108 "Model Zoo or TorchVision.")
109 )
110 parser.add_argument(
111 '--raw_train', default='', type=str,
112 help="Path to the training raw data."
113 )
114 parser.add_argument(
115 '--gt_train', default='', type=str,
116 help="Path to the training ground truth data."
117 )
118 parser.add_argument(
119 '--test_raw_path', default='', type=str,
120 help="Path to the testing raw data."
121 )
122 parser.add_argument(
123 '--test_gt_path', default='', type=str,
124 help="Path to the testing ground truth data."
125 )
126 parser.add_argument(
127 '--biapy_version', default='', type=str,
128 help="BiaPy version to use."
129 )
130
131 args = parser.parse_args()
132
133 if args.new_config:
134 workflow_map = {
135 "semantic": "SEMANTIC_SEG",
136 "instance": "INSTANCE_SEG",
137 "detection": "DETECTION",
138 "denoising": "DENOISING",
139 "sr": "SUPER_RESOLUTION",
140 "cls": "CLASSIFICATION",
141 "sr2": "SELF_SUPERVISED",
142 "i2i": "IMAGE_TO_IMAGE",
143 }
144 workflow_type = workflow_map[args.workflow]
145
146 if args.dims == "2d_stack":
147 ndim = "2D"
148 as_stack = True
149 elif args.dims == "2d":
150 ndim = "2D"
151 as_stack = True
152 elif args.dims == "3d":
153 ndim = "3D"
154 as_stack = False
155
156 config = download_yaml_template(
157 workflow_type, ndim, biapy_version=args.biapy_version
158 )
159
160 config["PROBLEM"]["TYPE"] = workflow_type
161 config["PROBLEM"]["NDIM"] = ndim
162 config["TEST"]["ANALIZE_2D_IMGS_AS_3D_STACK"] = as_stack
163
164 if args.model_source == "biapy":
165 config["MODEL"]["SOURCE"] = "biapy"
166 if args.model:
167 config["MODEL"]["LOAD_CHECKPOINT"] = True
168 config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = True
169 config.setdefault("PATHS", {})
170 config["PATHS"]["CHECKPOINT_FILE"] = args.model
171 else:
172 config["MODEL"]["LOAD_CHECKPOINT"] = False
173 config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = False
174 elif args.model_source == "bmz":
175 config["MODEL"]["SOURCE"] = "bmz"
176 config["MODEL"]["LOAD_CHECKPOINT"] = False
177 config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = False
178 config.setdefault("MODEL", {}).setdefault("BMZ", {})
179 config["MODEL"]["BMZ"]["SOURCE_MODEL_ID"] = args.model
180 elif args.model_source == "torchvision":
181 config["MODEL"]["SOURCE"] = "torchvision"
182 config["MODEL"]["LOAD_CHECKPOINT"] = False
183 config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = False
184 config["MODEL"]["TORCHVISION_MODEL_NAME"] = args.model
185
186 obj_size_map = {
187 "0-25": (256, 256),
188 "25-100": (256, 256),
189 "100-200": (512, 512),
190 "200-500": (512, 512),
191 "500+": (1024, 1024),
192 }
193 obj_size = obj_size_map[args.obj_size]
194
195 obj_slices_map = {
196 "": -1,
197 "1-5": 5,
198 "5-10": 10,
199 "10-20": 20,
200 "20-60": 40,
201 "60+": 80,
202 }
203 obj_slices = obj_slices_map[args.obj_slices]
204 if config["PROBLEM"]["NDIM"] == "2D":
205 config["DATA"]["PATCH_SIZE"] = obj_size + (args.img_channel,)
206 else:
207 assert obj_slices != -1, (
208 "For 3D problems, obj_slices must be specified."
209 )
210 config["DATA"]["PATCH_SIZE"] = (
211 (obj_slices,) + obj_size + (args.img_channel,)
212 )
213 config["DATA"]["PATCH_SIZE"] = str(config["DATA"]["PATCH_SIZE"])
214 else:
215 assert args.input_config_path, (
216 "Input configuration path must be specified when not "
217 "creating a new config."
218 )
219 with open(args.input_config_path, 'r', encoding='utf-8') as f:
220 config = yaml.safe_load(f)
221
222 if args.model:
223 config["MODEL"]["SOURCE"] = "biapy"
224 config["MODEL"]["LOAD_CHECKPOINT"] = True
225 config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = True
226 config.setdefault("PATHS", {})
227 config["PATHS"]["CHECKPOINT_FILE"] = args.model
228 else:
229 config["MODEL"]["LOAD_CHECKPOINT"] = False
230 config["MODEL"]["LOAD_MODEL_FROM_CHECKPOINT"] = False
231
232 if args.raw_train:
233 config["TRAIN"]["ENABLE"] = True
234 config["DATA"]["TRAIN"]["PATH"] = args.raw_train
235 config["DATA"]["TRAIN"]["GT_PATH"] = args.gt_train
236 else:
237 config["TRAIN"]["ENABLE"] = False
238
239 if args.test_raw_path:
240 config["TEST"]["ENABLE"] = True
241 config["DATA"]["TEST"]["PATH"] = args.test_raw_path
242 if args.test_gt_path:
243 config["DATA"]["TEST"]["LOAD_GT"] = True
244 config["DATA"]["TEST"]["GT_PATH"] = args.test_gt_path
245 else:
246 config["DATA"]["TEST"]["LOAD_GT"] = False
247 else:
248 config["TEST"]["ENABLE"] = False
249
250 # Always use safetensors in Galaxy
251 config["MODEL"]["OUT_CHECKPOINT_FORMAT"] = "safetensors"
252
253 config = tuple_to_list(config)
254
255 with open(args.out_config_path, 'w', encoding='utf-8') as f:
256 yaml.dump(config, f, default_flow_style=False)
257
258 print(f"YAML configuration written to {args.out_config_path}")
259
260
261 if __name__ == "__main__":
262 main()