This notebook shows how to use 3DeeCellTracker to track cells in ensemble mode.
The basic procedures:
Please run folloing codes according to the instructions
%load_ext autoreload
%autoreload 2
import os
import warnings
warnings.filterwarnings('ignore')
from IPython.core.display import display, HTML
from CellTracker.unet3d import unet3_b
from matplotlib.animation import FuncAnimation, ArtistAnimation
from CellTracker.tracker import Tracker
display(HTML("<style>.container { width:95% !important; }</style>"))
%matplotlib inline
Using TensorFlow backend.
Image parameters
Segmentation parameters
Tracking parameters
Paths
Multiple folders were automatically created to store data, model, and results
tracker = Tracker(
volume_num=80, siz_xyz=(168, 401, 128), z_xy_ratio=1, z_scaling=1, miss_frame=[79],
noise_level=200, min_size=50, beta_tk=1000, lambda_tk=0.00001, maxiter_tk=10, ensemble=20,
folder_path=os.path.abspath("./worm4"), image_name="raw_t%04i_z%04i.tif",
unet_model_file="unet3_pretrained_worm4.h5",ffn_model_file="ffn_pretrained.h5")
Following folders were made under: /home/wen/PycharmProjects/3DeeCellTracker worm4/data worm4/auto_vol1 worm4/manual_vol1 worm4/track_information worm4/models worm4/unet_cache worm4/track_results_EnsembleDstrbtMode worm4/anim worm4/models/unet_weights
Prepare images
Modify the segmentation parameters (optional)
tracker.set_segmentation(noise_level=200, min_size=50)
Segmentation parameters were not modified
Segment cells at volume 1
tracker.load_unet()
tracker.segment_vol1()
WARNING:tensorflow:From /home/wen/anaconda3/envs/3DCT-2/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead. WARNING:tensorflow:From /home/wen/anaconda3/envs/3DCT-2/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead. WARNING:tensorflow:From /home/wen/anaconda3/envs/3DCT-2/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:131: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead. WARNING:tensorflow:From /home/wen/anaconda3/envs/3DCT-2/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:133: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead. WARNING:tensorflow:From /home/wen/anaconda3/envs/3DCT-2/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead. Loaded the 3D U-Net model Load images with shape: (168, 401, 128) Segmented volume 1 and saved it
Draw the results of segmentation (Max projection)
anim_seg = tracker.draw_segresult(percentile_high=99.8)
Segmentation results (max projection):
Show segmentation in each layer
HTML(anim_seg)