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116 lines
5.0 KiB
Python
116 lines
5.0 KiB
Python
import os
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import pandas as pd
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from pathlib import Path
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from time import strptime
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code_dir = str(Path(os.getcwd()).parent)
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sites_csv_path = os.path.join(code_dir, "coastsnap_sites.csv")
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coastsnap_sites_csv = pd.read_csv(sites_csv_path)
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images_parent_dir = coastsnap_sites_csv.parent_directory[0]
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images_dir = os.path.join(images_parent_dir, "Images")
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stats_csv = pd.DataFrame(columns = ['site','# processed', '# photoshop', '# registered', 'stability', 'most recently deleted'] )
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print("Retrieving snapshot for:")
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for site in os.listdir(images_dir): # Loop through SITES
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i=0
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print(site)
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to_append = [site, 0, 0, 0, 0, 'None deleted']
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processed = False
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photoshop = False
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registered = False
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latest_deleted_image_found = False
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latest_registered_image_found = False
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site_path = os.path.join(images_dir, site)
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processed_path = os.path.join(site_path,'Processed')
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photoshop_path = os.path.join(site_path,'Photoshop')
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registered_path = os.path.join(site_path, 'Registered')
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try: # Check if site contains 'Processed' directory
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processed_years_list = os.listdir(processed_path)
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processed_years_list = [x for x in processed_years_list if len(x) == 4] # remove files that aren't years
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processed_years_list.reverse()
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processed = True
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except:
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continue
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try: # Check if site contains 'Processed' directory
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photoshop_years_list = os.listdir(photoshop_path)
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photoshop_years_list = [x for x in photoshop_years_list if len(x) == 4] # remove files that aren't years
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photoshop_years_list.reverse()
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photoshop = True
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except:
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continue
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try: # Check if site contains 'Processed' directory
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registered_years_list = os.listdir(registered_path)
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registered_years_list = [x for x in registered_years_list if len(x) == 4] # remove files that aren't years
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registered_years_list.reverse()
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registered = True
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except:
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continue
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if processed:
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i=0
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for year in processed_years_list: # Loop through YEARS
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processed_year_path = os.path.join(processed_path, year)
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processed_image_list = os.listdir(processed_year_path)
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processed_image_list.reverse()
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for image_filename in processed_image_list: # Loop through IMAGES
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i += 1
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to_append[1] = i
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if photoshop:
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i=0
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for year in photoshop_years_list: # Loop through YEARS
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year_path = os.path.join(photoshop_path, year)
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image_list = os.listdir(year_path)
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image_list.reverse()
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for image_filename in image_list: # Loop through IMAGES
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year_path = year_path.replace('Photoshop', 'Registered')
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registered_image_path = year_path + '/' + image_filename[:-4] + '_registered.jpg'
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# Finding the Latest Deleted Image Logic:
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# Iterate through 'Images/Processed'
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if os.path.isfile(registered_image_path): # Find the latest registered image.
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latest_registered_image_found = True # This is so the latest deleted image
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# isn't just the most recent image
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if (latest_registered_image_found and # Check if latest registered image has been found
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not latest_deleted_image_found and # Check if latest deleted image has already been found
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not os.path.isfile(registered_image_path) and # Check if photoshop registered image is also in 'Images/Registered'
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image_filename.endswith('.jpg')): # Sanity check: Make sure the file is an image
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latest_deleted_image_found = True
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filename_list = image_filename.split(".")
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date = filename_list[3].split("_")
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image_date = date[0] + '-' + '{:02d}'.format(strptime(filename_list[2],'%b').tm_mon) +'-'+ filename_list[5]
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to_append[5] = image_date
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i += 1
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to_append[2] = i
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if registered:
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i=0
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for year in registered_years_list: # Loop through YEARS
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registered_year_path = os.path.join(registered_path, year)
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registered_image_list = os.listdir(registered_year_path)
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registered_image_list.reverse()
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for image_filename in registered_image_list: # Loop through IMAGES
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i += 1
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to_append[3] = i
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stats_csv_length = len(stats_csv)
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stats_csv.loc[stats_csv_length] = to_append
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# Add site stability data (# registered / # processed)
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for i, row in stats_csv.iterrows():
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stability = "{0:.0%}".format(stats_csv.at[i, '# registered'] / stats_csv.at[i, '# processed'])
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stats_csv.at[i,'stability'] = stability
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stats_csv.set_index('site', inplace = True)
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output_file_path = os.path.join(code_dir, 'images_snapshot.csv')
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stats_csv.to_csv(output_file_path)
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