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@mustafaakin
Created February 18, 2019 20:14
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Finding blurred photos by album
import os
import sqlite3
import cv2
import numpy as np
def score(filename):
image = cv2.imread(filename)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
fm = cv2.Laplacian(gray, cv2.CV_64F).var()
return fm
if __name__ == '__main__':
p = "/Users/mustafa/Pictures/Photos Library.photoslibrary/resources/proxies/derivatives"
# Backup of the DB to not corrupt it
conn = sqlite3.connect('/Users/mustafa/photos.db')
# Find out the albums first
for row in conn.execute("SELECT RKAlbum.modelId, RKAlbum.name FROM RKAlbum GROUP BY 2"):
album_id = row[0]
album_name = row[1]
scores = []
# Select 100 Random photos from each album
query = """select RKVersion.modelId FROM RKAlbumVersion, RKVersion, RKMaster
WHERE RKVersion.modelId = RKAlbumVersion.versionId
AND RKMaster.modelId = RKVersion.masterId
AND RKAlbumVersion.albumId = %d
ORDER BY RANDOM()
LIMIT 100""" % album_id
for photo in conn.execute(query):
# Magic.. Kidding
# 0x831a --> derivatives/83/00/831a
h = hex(photo[0])
q = os.path.join(p, h[2:4], "00", h[2:])
try:
files = os.listdir(q)
for f in files:
if "mini" in f:
s = score(os.path.join(q, f))
scores.append(s)
break
except OSError:
# Sometimes files are not there
pass
print "Album :", album_name
print " Mean :", np.mean(scores)
print " StdDev :", np.std(scores)
print ""
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