<jupyter_start><jupyter_text>use:    dameter=40        flow_threshold=-0.4        cellprob_threshold=1        model=TN1        z-aspect=9.26<jupyter_code>def rescale(_im):
    _new_im = (_im - np.min(_im)) / (np.max(_im) - np.min(_im))
    return _new_im
    _new_im = _new_im / np.mean(_new_im) * 0.5
    print(np.mean(_new_im))
    _new_im = 1 - 1 / (1+_new_im)
    _new_im = (_new_im - np.min(_new_im)) / (np.max(_new_im) - np.min(_new_im))
    return _new_im<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '406007', 'license': 'MIT', 'n_tokens_mistral': 223, 'n_tokens_neox': 216, 'n_words': 30, 'path': 'MERFISH/MERLin_segmentation_cellpose2.ipynb', 'repo_name': 'shiwei23/Chromatin_Analysis_Scripts', 'size': '492'}