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io.py
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io.py
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"""
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Marius Pachitariu.
"""
import os, datetime, gc, warnings, glob, shutil, copy
from natsort import natsorted
import numpy as np
import cv2
import tifffile
import logging
import fastremap
from .. import utils, plot, transforms, models
from ..io import imread, imsave, outlines_to_text, add_model, remove_model, save_rois
from ..transforms import normalize99
try:
import qtpy
from qtpy.QtWidgets import QFileDialog
GUI = True
except:
GUI = False
try:
import matplotlib.pyplot as plt
MATPLOTLIB = True
except:
MATPLOTLIB = False
NCOLOR = False
# WIP to make GUI use N-color masks. Tricky thing is that only the display should be
# reduced to N colors; selection and editing should act on unique labels.
def _init_model_list(parent):
models.MODEL_DIR.mkdir(parents=True, exist_ok=True)
parent.model_list_path = models.MODEL_LIST_PATH
parent.model_strings = models.get_user_models()
def _add_model(parent, filename=None, load_model=True):
if filename is None:
name = QFileDialog.getOpenFileName(
parent, "Add model to GUI"
)
filename = name[0]
add_model(filename)
fname = os.path.split(filename)[-1]
parent.ModelChoose.addItems([fname])
parent.model_strings.append(fname)
if len(parent.model_strings) > 0:
parent.ModelButton.setStyleSheet(parent.styleUnpressed)
parent.ModelButton.setEnabled(True)
for ind, model_string in enumerate(parent.model_strings[:-1]):
if model_string == fname:
_remove_model(parent, ind=ind+1, verbose=False)
parent.ModelChoose.setCurrentIndex(len(parent.model_strings))
if load_model:
parent.model_choose(len(parent.model_strings))
def _remove_model(parent, ind=None, verbose=True):
if ind is None:
ind = parent.ModelChoose.currentIndex()
if ind > 0:
ind -= 1
parent.ModelChoose.removeItem(ind+1)
del parent.model_strings[ind]
# remove model from txt path
modelstr = parent.ModelChoose.currentText()
remove_model(modelstr)
if len(parent.model_strings) > 0:
parent.ModelChoose.setCurrentIndex(len(parent.model_strings))
else:
parent.ModelChoose.setCurrentIndex(0)
parent.ModelButton.setStyleSheet(parent.styleInactive)
parent.ModelButton.setEnabled(False)
else:
print('ERROR: no model selected to delete')
def _get_train_set(image_names):
""" get training data and labels for images in current folder image_names"""
train_data, train_labels, train_files = [], [], []
for image_name_full in image_names:
image_name = os.path.splitext(image_name_full)[0]
label_name = None
if os.path.exists(image_name + '_seg.npy'):
dat = np.load(image_name + '_seg.npy', allow_pickle=True).item()
masks = dat['masks'].squeeze()
if masks.ndim==2:
fastremap.renumber(masks, in_place=True)
label_name = image_name + '_seg.npy'
else:
print(f'GUI_INFO: _seg.npy found for {image_name} but masks.ndim!=2')
if label_name is not None:
train_files.append(image_name_full)
train_data.append(imread(image_name_full))
train_labels.append(masks)
return train_data, train_labels, train_files
def _load_image(parent, filename=None, load_seg=True):
""" load image with filename; if None, open QFileDialog """
if filename is None:
name = QFileDialog.getOpenFileName(
parent, "Load image"
)
filename = name[0]
manual_file = os.path.splitext(filename)[0]+'_seg.npy'
load_mask = False
if load_seg:
if os.path.isfile(manual_file) and not parent.autoloadMasks.isChecked():
_load_seg(parent, manual_file, image=imread(filename), image_file=filename)
return
elif os.path.isfile(os.path.splitext(filename)[0]+'_manual.npy'):
manual_file = os.path.splitext(filename)[0]+'_manual.npy'
_load_seg(parent, manual_file, image=imread(filename), image_file=filename)
return
elif parent.autoloadMasks.isChecked():
mask_file = os.path.splitext(filename)[0]+'_masks'+os.path.splitext(filename)[-1]
mask_file = os.path.splitext(filename)[0]+'_masks.tif' if not os.path.isfile(mask_file) else mask_file
load_mask = True if os.path.isfile(mask_file) else False
try:
print(f'GUI_INFO: loading image: {filename}')
image = imread(filename)
parent.loaded = True
except Exception as e:
print('ERROR: images not compatible')
print(f'ERROR: {e}')
if parent.loaded:
parent.reset()
parent.filename = filename
filename = os.path.split(parent.filename)[-1]
_initialize_images(parent, image, resize=parent.resize, X2=0)
parent.clear_all()
parent.loaded = True
parent.enable_buttons()
if load_mask:
_load_masks(parent, filename=mask_file)
def _initialize_images(parent, image, resize, X2):
""" format image for GUI """
parent.onechan=False
if image.ndim > 3:
# make tiff Z x channels x W x H
if image.shape[0]<4:
# tiff is channels x Z x W x H
image = np.transpose(image, (1,0,2,3))
elif image.shape[-1]<4:
# tiff is Z x W x H x channels
image = np.transpose(image, (0,3,1,2))
# fill in with blank channels to make 3 channels
if image.shape[1] < 3:
shape = image.shape
image = np.concatenate((image,
np.zeros((shape[0], 3-shape[1], shape[2], shape[3]), dtype=np.uint8)), axis=1)
if 3-shape[1]>1:
parent.onechan=True
image = np.transpose(image, (0,2,3,1))
elif image.ndim==3:
if image.shape[0] < 5:
image = np.transpose(image, (1,2,0))
if image.shape[-1] < 3:
shape = image.shape
#if parent.autochannelbtn.isChecked():
# image = normalize99(image) * 255
image = np.concatenate((image,np.zeros((shape[0], shape[1], 3-shape[2]),dtype=type(image[0,0,0]))), axis=-1)
if 3-shape[2]>1:
parent.onechan=True
image = image[np.newaxis,...]
elif image.shape[-1]<5 and image.shape[-1]>2:
image = image[:,:,:3]
#if parent.autochannelbtn.isChecked():
# image = normalize99(image) * 255
image = image[np.newaxis,...]
else:
image = image[np.newaxis,...]
img_min = image.min()
img_max = image.max()
parent.stack = image
parent.NZ = len(parent.stack)
parent.scroll.setMaximum(parent.NZ-1)
parent.stack = parent.stack.astype(np.float32)
parent.stack -= img_min
if img_max > img_min + 1e-3:
parent.stack /= (img_max - img_min)
parent.stack *= 255
if parent.NZ>1:
print('GUI_INFO: converted to float and normalized values to 0.0->255.0')
del image
gc.collect()
#parent.stack = list(parent.stack)
if parent.stack.ndim < 4:
parent.onechan=True
parent.stack = parent.stack[:,:,:,np.newaxis]
parent.imask=0
parent.Ly, parent.Lx = parent.stack.shape[1:3]
parent.layerz = 255 * np.ones((parent.Ly,parent.Lx,4), 'uint8')
print(parent.layerz.shape)
if parent.autobtn.isChecked():
print('GUI_INFO: normalization checked: computing saturation levels (and optionally filtered image)')
parent.compute_saturation()
elif len(parent.saturation) != parent.NZ:
parent.saturation = []
for r in range(3):
parent.saturation.append([])
for n in range(parent.NZ):
parent.saturation[-1].append([0, 255])
parent.sliders[r].setValue([0, 255])
parent.compute_scale()
parent.currentZ = int(np.floor(parent.NZ/2))
parent.scroll.setValue(parent.currentZ)
parent.zpos.setText(str(parent.currentZ))
parent.track_changes = []
def _load_seg(parent, filename=None, image=None, image_file=None):
""" load *_seg.npy with filename; if None, open QFileDialog """
if filename is None:
name = QFileDialog.getOpenFileName(
parent, "Load labelled data", filter="*.npy"
)
filename = name[0]
try:
dat = np.load(filename, allow_pickle=True).item()
dat['outlines']
parent.loaded = True
except:
parent.loaded = False
print('ERROR: not NPY')
return
parent.reset()
if image is None:
found_image = False
if 'filename' in dat:
parent.filename = dat['filename']
if os.path.isfile(parent.filename):
parent.filename = dat['filename']
found_image = True
else:
imgname = os.path.split(parent.filename)[1]
root = os.path.split(filename)[0]
parent.filename = root+'/'+imgname
if os.path.isfile(parent.filename):
found_image = True
if found_image:
try:
image = imread(parent.filename)
except:
parent.loaded = False
found_image = False
print('ERROR: cannot find image file, loading from npy')
if not found_image:
parent.filename = filename[:-11]
if 'img' in dat:
image = dat['img']
else:
print('ERROR: no image file found and no image in npy')
return
else:
parent.filename = image_file
if 'X2' in dat:
parent.X2 = dat['X2']
else:
parent.X2 = 0
if 'resize' in dat:
parent.resize = dat['resize']
elif 'img' in dat:
if max(image.shape) > max(dat['img'].shape):
parent.resize = max(dat['img'].shape)
else:
parent.resize = -1
_initialize_images(parent, image, resize=parent.resize, X2=parent.X2)
if 'chan_choose' in dat:
parent.ChannelChoose[0].setCurrentIndex(dat['chan_choose'][0])
parent.ChannelChoose[1].setCurrentIndex(dat['chan_choose'][1])
if 'outlines' in dat:
if isinstance(dat['outlines'], list):
# old way of saving files
dat['outlines'] = dat['outlines'][::-1]
for k, outline in enumerate(dat['outlines']):
if 'colors' in dat:
color = dat['colors'][k]
else:
col_rand = np.random.randint(1000)
color = parent.colormap[col_rand,:3]
median = parent.add_mask(points=outline, color=color)
if median is not None:
parent.cellcolors = np.append(parent.cellcolors, color[np.newaxis,:], axis=0)
parent.ncells+=1
else:
if dat['masks'].ndim==2:
dat['masks'] = dat['masks'][np.newaxis,:,:]
dat['outlines'] = dat['outlines'][np.newaxis,:,:]
if dat['masks'].min()==-1:
dat['masks'] += 1
dat['outlines'] += 1
parent.ncells = dat['masks'].max()
if 'colors' in dat and len(dat['colors'])==dat['masks'].max():
colors = dat['colors']
else:
colors = parent.colormap[:parent.ncells,:3]
parent.cellpix = dat['masks']
parent.outpix = dat['outlines']
parent.cellcolors = np.append(parent.cellcolors, colors, axis=0)
parent.draw_layer()
if 'est_diam' in dat:
parent.Diameter.setText('%0.1f'%dat['est_diam'])
parent.diameter = dat['est_diam']
parent.compute_scale()
if 'manual_changes' in dat:
parent.track_changes = dat['manual_changes']
print('GUI_INFO: loaded in previous changes')
if 'zdraw' in dat:
parent.zdraw = dat['zdraw']
else:
parent.zdraw = [None for n in range(parent.ncells)]
parent.loaded = True
print(f'GUI_INFO: {parent.ncells} masks found in {filename}')
else:
parent.clear_all()
parent.ismanual = np.zeros(parent.ncells, bool)
if 'ismanual' in dat:
if len(dat['ismanual']) == parent.ncells:
parent.ismanual = dat['ismanual']
if 'current_channel' in dat:
parent.color = (dat['current_channel']+2)%5
parent.RGBDropDown.setCurrentIndex(parent.color)
if 'flows' in dat:
parent.flows = dat['flows']
try:
if parent.flows[0].shape[-3]!=dat['masks'].shape[-2]:
Ly, Lx = dat['masks'].shape[-2:]
parent.flows[0] = cv2.resize(parent.flows[0].squeeze(), (Lx, Ly), interpolation=cv2.INTER_NEAREST)[np.newaxis,...]
parent.flows[1] = cv2.resize(parent.flows[1].squeeze(), (Lx, Ly), interpolation=cv2.INTER_NEAREST)[np.newaxis,...]
if parent.NZ==1:
parent.recompute_masks = True
else:
parent.recompute_masks = False
except:
try:
if len(parent.flows[0])>0:
parent.flows = parent.flows[0]
except:
parent.flows = [[],[],[],[],[[]]]
parent.recompute_masks = False
parent.enable_buttons()
parent.update_layer()
del dat
gc.collect()
def _load_masks(parent, filename=None):
""" load zeros-based masks (0=no cell, 1=cell 1, ...) """
if filename is None:
name = QFileDialog.getOpenFileName(
parent, "Load masks (PNG or TIFF)"
)
filename = name[0]
print(f'GUI_INFO: loading masks: {filename}')
masks = imread(filename)
outlines = None
if masks.ndim>3:
# Z x nchannels x Ly x Lx
if masks.shape[-1]>5:
parent.flows = list(np.transpose(masks[:,:,:,2:], (3,0,1,2)))
outlines = masks[...,1]
masks = masks[...,0]
else:
parent.flows = list(np.transpose(masks[:,:,:,1:], (3,0,1,2)))
masks = masks[...,0]
elif masks.ndim==3:
if masks.shape[-1]<5:
masks = masks[np.newaxis,:,:,0]
elif masks.ndim<3:
masks = masks[np.newaxis,:,:]
# masks should be Z x Ly x Lx
if masks.shape[0]!=parent.NZ:
print('ERROR: masks are not same depth (number of planes) as image stack')
return
_masks_to_gui(parent, masks, outlines)
del masks
gc.collect()
parent.update_layer()
parent.update_plot()
def _masks_to_gui(parent, masks, outlines=None):
""" masks loaded into GUI """
# get unique values
shape = masks.shape
masks = masks.flatten()
fastremap.renumber(masks, in_place=True)
masks = masks.reshape(shape)
masks = masks.astype(np.uint16) if masks.max()<2**16-1 else masks.astype(np.uint32)
parent.cellpix = masks
if parent.cellpix.ndim == 2:
parent.cellpix = parent.cellpix[np.newaxis,:,:]
print(f'GUI_INFO: {masks.max()} masks found')
# get outlines
if outlines is None: # parent.outlinesOn
parent.outpix = np.zeros_like(masks)
for z in range(parent.NZ):
outlines = utils.masks_to_outlines(masks[z])
parent.outpix[z] = outlines * masks[z]
if z%50==0 and parent.NZ > 1:
print('GUI_INFO: plane %d outlines processed'%z)
else:
parent.outpix = outlines
shape = parent.outpix.shape
_,parent.outpix = np.unique(parent.outpix, return_inverse=True)
parent.outpix = np.reshape(parent.outpix, shape)
parent.ncells = parent.cellpix.max()
colors = parent.colormap[:parent.ncells, :3]
print('GUI_INFO: creating cellcolors and drawing masks')
parent.cellcolors = np.concatenate((np.array([[255,255,255]]), colors), axis=0).astype(np.uint8)
parent.draw_layer()
if parent.ncells>0:
parent.toggle_mask_ops()
parent.ismanual = np.zeros(parent.ncells, bool)
parent.zdraw = list(-1*np.ones(parent.ncells, np.int16))
parent.update_layer()
parent.update_plot()
def _save_png(parent):
""" save masks to png or tiff (if 3D) """
filename = parent.filename
base = os.path.splitext(filename)[0]
if parent.NZ==1:
if parent.cellpix[0].max() > 65534:
print('GUI_INFO: saving 2D masks to tif (too many masks for PNG)')
imsave(base + '_cp_masks.tif', parent.cellpix[0])
else:
print('GUI_INFO: saving 2D masks to png')
imsave(base + '_cp_masks.png', parent.cellpix[0].astype(np.uint16))
else:
print('GUI_INFO: saving 3D masks to tiff')
imsave(base + '_cp_masks.tif', parent.cellpix)
def _save_flows(parent):
""" save flows and cellprob to tiff """
filename = parent.filename
base = os.path.splitext(filename)[0]
if len(parent.flows) > 0:
imsave(base + '_cp_flows.tif', parent.flows[4][:-1])
imsave(base + '_cp_cellprob.tif', parent.flows[4][-1])
def _save_rois(parent):
""" save masks as rois in .zip file for ImageJ """
filename = parent.filename
if parent.NZ == 1:
print(f'GUI_INFO: saving {parent.cellpix[0].max()} ImageJ ROIs to .zip archive.')
save_rois(parent.cellpix[0], parent.filename)
else:
print('ERROR: cannot save 3D outlines')
def _save_outlines(parent):
filename = parent.filename
base = os.path.splitext(filename)[0]
if parent.NZ==1:
print('GUI_INFO: saving 2D outlines to text file, see docs for info to load into ImageJ')
outlines = utils.outlines_list(parent.cellpix[0])
outlines_to_text(base, outlines)
else:
print('ERROR: cannot save 3D outlines')
def _save_sets_with_check(parent):
""" Save masks and update *_seg.npy file. Use this function when saving should be optional
based on the disableAutosave checkbox. Otherwise, use _save_sets """
if not parent.disableAutosave.isChecked():
_save_sets(parent)
def _save_sets(parent):
""" save masks to *_seg.npy. This function should be used when saving
is forced, e.g. when clicking the save button. Otherwise, use _save_sets_with_check
"""
filename = parent.filename
base = os.path.splitext(filename)[0]
flow_threshold, cellprob_threshold = parent.get_thresholds()
if parent.NZ > 1 and parent.is_stack:
np.save(base + '_seg.npy',
{'outlines': parent.outpix,
'colors': parent.cellcolors[1:],
'masks': parent.cellpix,
'current_channel': (parent.color-2)%5,
'filename': parent.filename,
'flows': parent.flows,
'zdraw': parent.zdraw,
'model_path': parent.current_model_path if hasattr(parent, 'current_model_path') else 0,
'flow_threshold': flow_threshold,
'cellprob_threshold': cellprob_threshold
})
else:
np.save(base + '_seg.npy',
{'outlines': parent.outpix.squeeze(),
'colors': parent.cellcolors[1:],
'masks': parent.cellpix.squeeze(),
'chan_choose': [parent.ChannelChoose[0].currentIndex(),
parent.ChannelChoose[1].currentIndex()],
'filename': parent.filename,
'flows': parent.flows,
'ismanual': parent.ismanual,
'manual_changes': parent.track_changes,
'model_path': parent.current_model_path if hasattr(parent, 'current_model_path') else 0,
'flow_threshold': flow_threshold,
'cellprob_threshold': cellprob_threshold})
#print(parent.point_sets)
print('GUI_INFO: %d ROIs saved to %s'%(parent.ncells, base + '_seg.npy'))