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annotate cp_segmentation.py @ 2:e5370bb71633 draft default tip

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit 5846f23282167df28e6cc00e1bda31523b66b5b4
author bgruening
date Sat, 15 Mar 2025 17:23:55 +0000
parents 1857781df226
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4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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1 import argparse
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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2 import json
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3 import os
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4 import warnings
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6 # Make sure, that `MKL_NUM_THREADS` is set to 1, to ensure reproducibility:
e5370bb71633 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit 5846f23282167df28e6cc00e1bda31523b66b5b4
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7 # https://forum.image.sc/t/reproducibility-how-we-spent-years-building-containers-and-then-mkl-decided-to-screw-our-results/109599
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8 if str(os.environ['MKL_NUM_THREADS']) != '1':
e5370bb71633 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit 5846f23282167df28e6cc00e1bda31523b66b5b4
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9 warnings.warn('MKL_NUM_THREADS must be set to 1 to ensure reproducibility, and will be adjusted accordingly for now.')
e5370bb71633 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit 5846f23282167df28e6cc00e1bda31523b66b5b4
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10 os.environ['MKL_NUM_THREADS'] = '1'
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e5370bb71633 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit 5846f23282167df28e6cc00e1bda31523b66b5b4
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12 # Load the remaining packages *after* adjusting `MKL_NUM_THREADS` (this likely necessary for it to take effect)
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13 import matplotlib.pyplot as plt
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14 import numpy as np
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15 import skimage.io
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16 import torch
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17 from cellpose import models, plot, transforms
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19 # Apply PyTorch guidelines for reproducibility
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20 torch.backends.cudnn.benchmark = True
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21 torch.backends.cudnn.deterministic = True
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22 torch.manual_seed(0)
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23
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25 def main(inputs, img_path, img_format, output_dir):
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26 """
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27 Parameter
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28 ---------
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29 inputs : str
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30 File path to galaxy tool parameter
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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31 img_path : str
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32 File path for the input image
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33 img_format : str
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34 One of the ['ome.tiff', 'tiff', 'png', 'jpg']
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35 output_dir : str
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36 Folder to save the outputs.
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37 """
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38 warnings.simplefilter('ignore')
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39 np.random.seed(42)
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40 with open(inputs, 'r') as param_handler:
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41 params = json.load(param_handler)
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42
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43 gpu = params['use_gpu']
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44 model_type = params['model_type']
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45 chan = params['chan']
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46 chan2 = params['chan2']
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47 chan_first = params['chan_first']
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48 if chan is None:
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49 channels = None
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50 else:
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51 channels = [int(chan), int(chan2) if chan2 is not None else None]
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52
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53 options = params['options']
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54
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55 img = skimage.io.imread(img_path)
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56
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57 print(f"Image shape: {img.shape}")
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58 # transpose to Ly x Lx x nchann and reshape based on channels
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59 if img_format.endswith('tiff'):
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60 img = np.transpose(img, (1, 2, 0))
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61 img = transforms.reshape(img, channels=channels, chan_first=chan_first)
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62
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63 print(f"Image shape: {img.shape}")
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64 model = models.Cellpose(gpu=gpu, model_type=model_type)
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65 masks, flows, styles, diams = model.eval(img, channels=channels, **options)
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66
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67 # save masks to tiff
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68 with warnings.catch_warnings():
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69 warnings.simplefilter("ignore")
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70 skimage.io.imsave(os.path.join(output_dir, 'cp_masks.tif'),
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71 masks.astype(np.uint16))
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72
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73 # make segmentation show #
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74 if params['show_segmentation']:
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75 img = skimage.io.imread(img_path)
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76 # uniform image
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77 if img_format.endswith('tiff'):
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78 img = np.transpose(img, (1, 2, 0))
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79 img = transforms.reshape(img, channels=channels, chan_first=chan_first)
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80
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81 maski = masks
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82 flowi = flows[0]
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83 fig = plt.figure(figsize=(12, 3))
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84 # can save images (set save_dir=None if not)
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85 plot.show_segmentation(fig, img, maski, flowi, channels=channels)
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86 fig.savefig(os.path.join(output_dir, 'segm_show.png'), dpi=300)
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87 plt.close(fig)
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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88
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89
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90 if __name__ == '__main__':
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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91 aparser = argparse.ArgumentParser()
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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92 aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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93 aparser.add_argument("-p", "--img_path", dest="img_path")
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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94 aparser.add_argument("-f", "--img_format", dest="img_format")
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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95 aparser.add_argument("-O", "--output_dir", dest="output_dir")
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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96 args = aparser.parse_args()
4ddb0af5a806 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/cellpose commit e80ca9b0e2e6f7ae94371170d0a672f46f2d9c3c
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97
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98 main(args.inputs, args.img_path, args.img_format, args.output_dir)