Mercurial > repos > goeckslab > image_learner

annotate image_learner_cli.py @ 13:1a9c42974a5a draft default tip

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planemo upload for repository https://github.com/goeckslab/gleam.git commit 9f96da4ea7ab3b572af86698ff51b870125cd674
author goeckslab
date Fri, 21 Nov 2025 17:35:00 +0000
parents bcfa2e234a80
children
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54b871dfc51e planemo upload for repository https://github.com/goeckslab/gleam.git commit b7411ff35b6228ccdfd36cd4ebd946c03ac7f7e9
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diff changeset
1 import argparse
54b871dfc51e planemo upload for repository https://github.com/goeckslab/gleam.git commit b7411ff35b6228ccdfd36cd4ebd946c03ac7f7e9
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2 import logging
54b871dfc51e planemo upload for repository https://github.com/goeckslab/gleam.git commit b7411ff35b6228ccdfd36cd4ebd946c03ac7f7e9
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3 import os
54b871dfc51e planemo upload for repository https://github.com/goeckslab/gleam.git commit b7411ff35b6228ccdfd36cd4ebd946c03ac7f7e9
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4 import sys
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5 from pathlib import Path
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6
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7 import matplotlib
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8 from constants import MODEL_ENCODER_TEMPLATES
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9 from image_workflow import ImageLearnerCLI
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10 from ludwig_backend import LudwigDirectBackend
bcfa2e234a80 planemo upload for repository https://github.com/goeckslab/gleam.git commit 96bab8325992d16fcaad8e0a4dc4c62b00e2abc2
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11 from split_data import SplitProbAction
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12 from utils import argument_checker, parse_learning_rate
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13
11
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14 # Set matplotlib backend after imports
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15 matplotlib.use('Agg')
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16
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17 # --- Logging Setup ---
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18 logging.basicConfig(
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19 level=logging.INFO,
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20 format="%(asctime)s %(levelname)s %(name)s: %(message)s",
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21 )
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22 logger = logging.getLogger("ImageLearner")
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23
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25 def main():
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26 parser = argparse.ArgumentParser(
1
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27 description="Image Classification Learner with Pluggable Backends",
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28 )
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29 parser.add_argument(
1
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30 "--csv-file",
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31 required=True,
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32 type=Path,
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33 help="Path to the input metadata file (CSV, TSV, etc)",
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34 )
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35 parser.add_argument(
1
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36 "--image-zip",
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37 required=True,
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38 type=Path,
11
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39 help="Path to the images ZIP or a directory containing images",
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40 )
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41 parser.add_argument(
1
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42 "--model-name",
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43 required=True,
0
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44 choices=MODEL_ENCODER_TEMPLATES.keys(),
1
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45 help="Which model template to use",
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54b871dfc51e planemo upload for repository https://github.com/goeckslab/gleam.git commit b7411ff35b6228ccdfd36cd4ebd946c03ac7f7e9
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46 )
54b871dfc51e planemo upload for repository https://github.com/goeckslab/gleam.git commit b7411ff35b6228ccdfd36cd4ebd946c03ac7f7e9
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47 parser.add_argument(
1
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48 "--use-pretrained",
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49 action="store_true",
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50 help="Use pretrained weights for the model",
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51 )
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52 parser.add_argument(
1
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53 "--fine-tune",
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54 action="store_true",
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55 help="Enable fine-tuning",
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56 )
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57 parser.add_argument(
1
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58 "--epochs",
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59 type=int,
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60 default=10,
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61 help="Number of training epochs",
0
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62 )
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63 parser.add_argument(
1
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64 "--early-stop",
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65 type=int,
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66 default=5,
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67 help="Early stopping patience",
0
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68 )
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69 parser.add_argument(
1
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70 "--batch-size",
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71 type=int,
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72 help="Batch size (None = auto)",
0
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73 )
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74 parser.add_argument(
1
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75 "--output-dir",
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76 type=Path,
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77 default=Path("learner_output"),
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78 help="Where to write outputs",
0
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79 )
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80 parser.add_argument(
1
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81 "--validation-size",
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82 type=float,
8
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83 default=0.15,
1
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84 help="Fraction for validation (0.0–1.0)",
0
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85 )
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86 parser.add_argument(
1
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87 "--preprocessing-num-processes",
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88 type=int,
0
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89 default=max(1, os.cpu_count() // 2),
1
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90 help="CPU processes for data prep",
0
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91 )
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92 parser.add_argument(
1
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93 "--split-probabilities",
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94 type=float,
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95 nargs=3,
0
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96 metavar=("train", "val", "test"),
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97 action=SplitProbAction,
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98 default=[0.7, 0.1, 0.2],
2
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99 help=(
9
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100 "Random split proportions (e.g., 0.7 0.1 0.2).Only used if no split column."
2
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101 ),
0
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102 )
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103 parser.add_argument(
1
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104 "--random-seed",
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105 type=int,
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106 default=42,
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107 help="Random seed used for dataset splitting (default: 42)",
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108 )
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109 parser.add_argument(
1
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110 "--learning-rate",
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111 type=parse_learning_rate,
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112 default=None,
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113 help="Learning rate. If not provided, Ludwig will auto-select it.",
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114 )
2
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115 parser.add_argument(
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116 "--augmentation",
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117 type=str,
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118 default=None,
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119 help=(
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120 "Comma-separated list (in order) of any of: "
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121 "random_horizontal_flip, random_vertical_flip, random_rotate, "
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122 "random_blur, random_brightness, random_contrast. "
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123 "E.g. --augmentation random_horizontal_flip,random_rotate"
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124 ),
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125 )
8
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126 parser.add_argument(
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127 "--image-resize",
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128 type=str,
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129 choices=[
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130 "original", "96x96", "128x128", "160x160", "192x192", "220x220",
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131 "224x224", "256x256", "299x299", "320x320", "384x384", "448x448", "512x512"
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132 ],
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133 default="original",
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134 help="Image resize option. 'original' keeps images as-is, other options resize to specified dimensions.",
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135 )
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136 parser.add_argument(
8
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137 "--threshold",
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138 type=float,
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139 default=None,
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140 help=(
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141 "Decision threshold for binary classification (0.0–1.0)."
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142 "Overrides default 0.5."
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143 ),
8
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144 )
11
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145
0
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146 args = parser.parse_args()
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147
12
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148 argument_checker(args, parser)
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149
0
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150 backend_instance = LudwigDirectBackend()
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151 orchestrator = ImageLearnerCLI(args, backend_instance)
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152
0
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153 exit_code = 0
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154 try:
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155 orchestrator.run()
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156 logger.info("Main script finished successfully.")
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157 except Exception as e:
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158 logger.error(f"Main script failed.{e}")
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159 exit_code = 1
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160 finally:
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161 sys.exit(exit_code)
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162
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163
1
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164 if __name__ == "__main__":
0
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165 try:
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166 import ludwig
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167
0
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168 logger.debug(f"Found Ludwig version: {ludwig.globals.LUDWIG_VERSION}")
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169 except ImportError:
1
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170 logger.error(
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171 "Ludwig library not found. Please ensure Ludwig is installed "
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172 "('pip install ludwig[image]')"
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173 )
0
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174 sys.exit(1)
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175
0
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176 main()