Yu-AnChen

For large files, submit multiple parallel jobs of omero import

P1. find all the files to be uploaded, write the file paths to a csv (mosaics.csv), and review the list. For example, type the following in the terminal to save matching files to mosaics.csv

find /n/scratch3/users/y/yc296/216-OMS_2022MAR-2022MAR/mcmicro -type f -wholename */registration/*.ome.tif | sort >> mosaics.csv
find /n/scratch3/users/y/yc296/216-OMS_2022MAR-2022MAR/mcmicro -type f -wholename */qc/*.ome.tif | sort >> mosaics.csv

P2. follow step 1 and 3 here

Yu-AnChen

javascript:(function(){
 let infotab = document.getElementById('infoTab').children[0].children[2];
 let channels = infotab.children[0].children[1].children[0].lastElementChild.textContent.trim().split(', ');
 let channelsliders = document.getElementById('channel_sliders').children[0];
 for(i=0;i<channels.length;i++) {
     let p = document.createTextNode(channels[i]);
     let br = document.createElement('br');
     channelsliders.children[i].insertBefore(br,channelsliders.children[i].firstChild);
     channelsliders.children[i].insertBefore(p,channelsliders.children[i].firstChild);
 }

Yu-AnChen

var project_number = 111;
var exp_number = 1;
var exp_name = '168-tumor';

var href = `https://reagenttracker.hms.harvard.edu/api/v0/imaging_cycle/${project_number}/${exp_number}`;
var csv_name = `${exp_name}-${project_number}-${exp_number}`;
var use_actual_cycles = false;

Promise
	.all([parse_vocab(), get_exp(href)])

Yu-AnChen

# ref https://forum.image.sc/t/omero-py-how-to-get-tiles-at-different-zoom-level-pyramidal-image/

import numpy as np
from omero.gateway import BlitzGateway
from omero.model import enums as omero_enums
import omero

def connect_hms_omero(session_id):
    SESSION_ID = session_id
    HOST = 'omero-app.hms.harvard.edu'

Yu-AnChen

import argparse
import json
import sys

from omero.gateway import BlitzGateway
from omero.cli import cli_login
from omero.model import StatsInfoI
from omero.rtypes import rdouble

Yu-AnChen

import tifffile
import numpy as np

def per_channel_per_tile(img, tile=(1024, 1024)):
    num_channels, num_rows, num_columns = img.shape
    h, w = tile
    for c in range(num_channels):
        for y in range(0, num_rows, h):
            for x in range(0, num_columns, w):
                yield img[c, y:y+h, x:x+w]

Yu-AnChen

# https://forum.image.sc/t/numpy-to-imageplus-imageplus-to-numpy-conversion-with-pyimagej/29399/1
import imagej
import numpy as np

# initialize imagej
ij = imagej.init()

import jnius
# get Java class representations
BackgroundSubtracter = jnius.autoclass(

Yu-AnChen

import cv2
import matplotlib.patches as mpatches
import copy
import numpy as np
import matplotlib.pyplot as plt

def binary_to_patches(binary_img):
    assert np.unique(binary_img).shape[0] == 2, \
        'Input image must be a binary image'
    contours, _ = cv2.findContours(

Yu-AnChen

import synapseclient
import pathlib
from synapseclient import Folder, File


exclude_folders = (
    '.nextflow',
    'probability-maps',
    'qc',
    'registration',

Yu-AnChen

var imgIds = [
    1203716, 1203756, 1203720,
];
const omeroUrls = {
    hms: 'https://omero.hms.harvard.edu',
    idp: 'https://idp.tissue-atlas.org'
};
// choose omero instance between the HMS and the IDP OMERO
const whichOmero = 'hms';