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Python

import numpy as np
from datetime import datetime, timedelta
import sys
from time import strptime
from PIL import Image, ImageFont
import pandas as pd
import openpyxl
def divide_chunks(l, n):
"""
Splits a list into chunks of length n. Used to process the images in chunks.
"""
for i in range(0, len(l), n):
yield l[i : i + n]
# Sourced from https://gist.github.com/victorkristof/b9d794fe1ed12e708b9d
def datenum_to_datetime(datenum):
"""
Convert Matlab datenum into Python datetime.
:param datenum: Date in datenum format
:return: Datetime object corresponding to datenum.
"""
days = datenum % 1
hours = days % 1 * 24
minutes = hours % 1 * 60
seconds = np.round(minutes % 1 * 60)
return datetime.fromordinal(int(datenum)) \
+ timedelta(days=int(days)) \
+ timedelta(hours=int(hours)) \
+ timedelta(minutes=int(minutes)) \
+ timedelta(seconds=int(seconds)) \
- timedelta(days=366)
# Sourced from https://stackoverflow.com/questions/32237862/find-the-closest-date-to-a-given-date
def nearest(all_dates, target_date_raw):
abs_deltas_from_target_date = np.absolute(all_dates - target_date_raw)
index_of_min_delta_from_target_date = np.argmin(abs_deltas_from_target_date)
closest_date = all_dates[index_of_min_delta_from_target_date]
return closest_date
def progressbar(it, prefix="", size=60, out=sys.stdout): # Python3.3+
count = len(it)
def show(j):
x = int(size*j/count)
print("{}[{}{}] {}/{}".format(prefix, u"#"*x, "."*(size-x), j, count),
end='\r', file=out, flush=True)
show(0)
for i, item in enumerate(it):
yield item
show(i+1)
print("\n", flush=True, file=out)
def get_site_tide_data(images_parent_dir, site):
print("Retrieving tide data")
# Retrieve tide data for the given site
db = openpyxl.load_workbook(images_parent_dir + "/Database/CoastSnapDB.xlsx")
beach_data = db[site]
tide_filename = beach_data["B24"].value
if tide_filename == 'NO_TIDE.mat':
return False
tide_filename_pkl = tide_filename[:-4] + '.pkl'
tides_path = images_parent_dir + '/Tide Data/Tide_Data_Python/' + tide_filename_pkl
tides_df = pd.read_pickle(tides_path)
return tides_df
class RegisteredImage():
def __init__(self, pathname, filename, registered_pathname):
self.pathname = pathname
self.filename = filename
self.registered_pathname = registered_pathname
filename_list = filename.split(".")
date = filename_list[3].split("_")
if 'snap' in filename_list:
self.contributor = filename_list[8] # Mitch filename format
else:
self.contributor = filename_list[6] # Leaman filename format
self.site = filename_list[6]
self.posix_time = filename_list[0]
self.timezone = filename_list[4]
self.year = filename_list[5]
self.month = '{:02d}'.format(strptime(filename_list[2],'%b').tm_mon) # Ensure 2-digit format
self.day = date[0]
self.hour = date[1]
self.minute = date[2]
self.second = date[3]
self.tide = None
self.tag = None
self.width = None
self.height = None
self.font = None
self.large_filename = False
def get_tide(self, tides_df):
# Account for daylight savings
# ASSUMPTION: All .mat tide files are either AEST or AEDT
if self.timezone == 'AEDT':
self.hour = str(int(self.hour) - 1)
date_string = self.year + '-' + self.month + '-' + self.day + ' ' + self.hour + ':' + self.minute + ':' + self.second
img_datetime = datetime.strptime(date_string, "%Y-%m-%d %H:%M:%S") # Image date/time as a datetime object
tide_date = nearest(tides_df['time'], img_datetime)
tide = tides_df.loc[tides_df['time'] == tide_date, 'tide level']
tide = tide.iloc[0]
self.tide = "{:.2f}".format(tide)
def create_tag(self):
# Create image tag
hour = self.hour.zfill(2)
minute = self.minute.zfill(2)
if self.tide: # Tag with tide data
tide = self.tide
if float(self.tide) >= 0:
tide = '+' + self.tide
tag = ('Date:' + self.year + '/' + self.month + '/' + self.day +
' Time:' + hour + ':' + minute +
' Tide:' + tide + 'm AHD' +
' Contributor:' + self.contributor)
if(self.font.getsize(tag)[0] > self.width): # Check if text is wider than the image
self.large_filename = True
tag = ('Date:' + self.year + '/' + self.month + '/' + self.day +
' Time:' + hour + ':' + minute +
' Tide:' + tide + 'm AHD' + '\n' +
'Contributor:' + self.contributor)
self.tag = tag
else: # Tag without tide data
tag = ('Date:' + self.year + '/' + self.month + '/' + self.day +
' Time:' + hour + ':' + minute +
' Contributor:' + self.contributor)
if(self.font.getsize(tag)[0] > self.width): # Check if text is wider than the image
self.large_filename = True
tag = ('Date:' + self.year + '/' + self.month + '/' + self.day +
' Time:' + hour + ':' + minute + '\n' +
'Contributor:' + self.contributor)
self.tag = tag
def get_dimensions(self):
image = Image.open(self.pathname)
# White Text Box
self.width, self.height = image.size
def get_font(self):
image = Image.open(self.pathname)
fontsize = 1
if self.tide:
img_fraction = 0.95
else:
img_fraction = 0.85
font = ImageFont.truetype("fonts/LiberationMono.ttf", fontsize)
generic_large_tag = "1641775682.Mon.Jan.10_11_48_02.AEDT.2022.byron.snap.KateThornborough123"
while font.getsize(generic_large_tag)[0] < img_fraction*image.size[0]:
# iterate until the text size is just larger than the criteria
fontsize += 1
font = ImageFont.truetype("fonts/LiberationMono.ttf", fontsize)
self.font = ImageFont.truetype("fonts/LiberationMono.ttf", fontsize)