/
crop_wells.py
114 lines (96 loc) · 4.67 KB
/
crop_wells.py
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import numpy as np
from os.path import exists
from os import makedirs
import read_input as rin
import filtering
import math
import crop_interface as interface
import os
import cv2 as cv
import matplotlib.pyplot as plt
# well size params are set for a 5496 × 3672 image
# if wellNum parameter is not specified or set to -1, all wells will be cropped
def crop_one(plateFolder, start_frame, end_frame, x_start, y_start, well_width, well_height, x_end=None, y_end=None, x_adj=0, y_adj=0, wells=-1, image_type=".png"):
if type(wells) is not list:
wells = [wells]
wells = list(wells)
outputPath = plateFolder + "/results"
if os.path.exists(outputPath) is False:
# create a folder where the script output would be stored
# if it does not yet exists
os.makedirs(outputPath)
# plateFolder = "/Users/Arina/Desktop/02" + str(i + 1) #TODO change later when we want to look at more plates
# wellFolder = './well_data/input/' + output_name + '/well_' + str(i+1)
if exists(plateFolder) is False:
makedirs(plateFolder)
for j in range(48):
wellFolder = outputPath + '/well_' + str(j + 1)
if exists(wellFolder) is False:
makedirs(wellFolder)
# filepath = filepath + dataset_name + "/"
# Need to establish well plate naming convention and change the filepath here
imgs = rin.read_input(start_frame=start_frame,
end_frame=end_frame, filepath=plateFolder)
print("start cropping")
# for frame, img in enumerate(imgs[plate - 1]):
for frame, img in enumerate(imgs):
if img is not None:
counter = 0
# for i in range(y_start, y_end, well_width):
# for j in range(x_start, x_end, well_width):
for i in range(y_start, y_start+6*(well_height+y_adj), well_height+y_adj):
for j in range(x_start, x_start+(8*well_width+x_adj), well_width+x_adj):
counter += 1
print("\n\ntype", type(wells))
print(wells)
if (-1 in wells) or (counter in wells):
x_1 = x_start + (j - x_start)
y_1 = y_start + (i - y_start)
y_2 = y_1 + well_height
x_2 = x_1 + well_height
cropped = img[y_1:y_2, x_1:x_2]
impath = outputPath + "/" + "well_" + \
str(counter) + "/" + "croppedImage" + \
"_" + str(start_frame + frame) + image_type
cv.imwrite(impath, cropped)
#print("writing", impath)
del imgs # explicitly free up memory
def crop(x_start=250, y_start=35, x_end=1840, y_end=1170, well_width=190, well_height=190, start_frame=1, end_frame=100):
# Select the corner wells. Press Q to quit. Press R to restart.
print("Please select the corner wells")
refPts = interface.getPoints(plateFolder)
x_start, y_start = int(
refPts[0][0]-0.5*well_width), int(refPts[0][1]-0.5*well_height)
x_end, y_end = int(
refPts[1][0]+0.5*well_width), int(refPts[2][1]+0.5*well_height)
x_adj = math.ceil((refPts[4][0] - refPts[1][0])/8) # (x_4-x_2)/8
y_adj = math.ceil((refPts[1][1] - refPts[0][1])/8) # (y_2-y_1)/6
for i in range(15): # TODO: change that!!!!! 15 is bc we process 100 at once
crop_one(plateFolder=plateFolder, start_frame=start_frame, end_frame=end_frame, x_start=x_start, y_start=y_start, x_adj=x_adj, y_adj=y_adj, well_width=well_width, well_height=well_height, wells=wells, image_type=".png")
start_frame = end_frame
end_frame = end_frame + 100
if __name__ == "__main__":
####### SPECIFY THE PLATE FOLDER ######
plateFolder = '/Users/arina/Desktop/Neuro98 articles + misc/2021_08_12 Arina 3 chem scrunching/18'
# change these if necessary
image_type = ".png"
outputPath = plateFolder + "/results"
###### CHANGE THIS IF YOU WANT TO CROP ONLY SPECIFIC WELLS ####
# e.g. To crop wells 1 and 2 only, replace the line below with
# wells = [1,2]
wells = np.arange(1, 49, 1).tolist()
start_frame = 1
end_frame = 100
# end_frame - start_frame gives us the number of frames
# to be loaded AT ONCE for internal processing.
# 100-150 is optimal for speed (more frames is too memory intense)
# Well cropping params
# you can try to adjust these if the plate is severely misalligned
x_start = 250
y_start = 35
x_end = 1840
y_end = 1170
well_width = 190
well_height = 190
crop(x_start=x_start, y_start=y_start, x_end=x_end, y_end=y_end,
well_width=well_width, well_height=well_height)