画像のヒストグラム値を含む2つの辞書を作成しました。各辞書には、キーとして画像ファイルのファイル名があり、値としてまとめられた3つの1次元ベクトルのリストがあります。
例: {'someFileName.jpg' : ['forecolor=2,3,5,5,6','edge=2,4,5','texture=5,4,3']}
これが私の辞書の1つの実際の表現です:
Dictionary1
{'/Users/images/Transcend-8GB-Class-10-SDHC-Flash-Memory-Card.jpg': ['fcolor=2,4,14,5,0,0,0,0,0,0,0,0,0,0,12,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,6,0,0,0,0,1,0,0,0,0,0,0,0,0,0,20,9,0,0,0,2,2,0,0,0,0,0,0,0,0,0,13,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,10,8,0,0,0,1,2,0,0,0,0,0,0,0,0,0,17,17,0,0,0,3,6,0,0,0,0,0,0,0,0,0,7,5,0,0,0,2,0,0,0,0,0,0,0,0,0,0,4,3,0,0,0,1,1,0,0,0,0,0,0,0,0,0,6,6,0,0,0,2,3', 'edge=1,252,1,32,124,194,63,252,67,15,240,1,7,244,66,47,0,192,63', 'texture=1,78,27,37,13,6,6,7,78']}
Dictionary2
{'/Users/images/kodax-camera-M531.jpg': ['fcolor=2,74,6,20,30,1,2,0,1,0,0,0,1,3,2,0,0,0,0,0,1,1,1,0,0,2,0,0,0,2,2,0,0,0,0,0,2,2,1,0,0,5,0,0,0,1,4,0,0,0,0,0,2,2,1,0,0,1,0,0,0,3,1,0,0,0,0,0,1,1,0,0,0,3,0,0,0,1,2,0,0,0,0,0,2,2,1,0,0,4,0,0,0,0,5,0,0,0,0,0,2,1,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0', 'edge=1,4,1,88,128,22,8,39,25,142,230,226,31,60,64,255,252,12,76', 'texture=1,15,32,31,28,19,16,12,98']}
私の最終目標は、これらのディクショナリのうち2つをメソッドに渡し、実際にcosign値を実行することです。
例:各ディクショナリには値としてリストがあるので、各ディクショナリキーについて、dictionary1のkey1、velu1とdictionary2 key1、value1の間でベクトル乗算を実行します。
私はベクトル乗算関数を持っているので、適切に反復する方法を理解しようとしているので、yield関数を使用することを考えていましたが、実際に試しても機能しませんでした。これは私がこれまでに持っているものです:
def cosignSimilarity(image1VectorDict, image2VectorDict):
for image1Key, image2Value in image1VectorDict.iteritems():
print image1Key
for aValue in image1Value:
print aValue
for image2Key, image2Value in image2VectorDict.iteritems():
for eValue in image2Value:
print aValue
print "\n"
print eValue
参考までに:私はコサインの計算について助けを求めていません。
これは、ある辞書から別の辞書にキーを分離できれば、現在のコードがデータを吐き出している方法です。その後、正弦値の計算などの残りの作業を行うことができます。
First Dictionary
{'/Users/test/Transcend-8GB-Class-10-SDHC-Flash-Memory-Card.jpg': ['fcolor=2,4,14,5,0,0,0,0,0,0,0,0,0,0,12,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,6,0,0,0,0,1,0,0,0,0,0,0,0,0,0,20,9,0,0,0,2,2,0,0,0,0,0,0,0,0,0,13,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,10,8,0,0,0,1,2,0,0,0,0,0,0,0,0,0,17,17,0,0,0,3,6,0,0,0,0,0,0,0,0,0,7,5,0,0,0,2,0,0,0,0,0,0,0,0,0,0,4,3,0,0,0,1,1,0,0,0,0,0,0,0,0,0,6,6,0,0,0,2,3', 'edge=1,252,1,32,124,194,63,252,67,15,240,1,7,244,66,47,0,192,63', 'texture=1,78,27,37,13,6,6,7,78']}
------------------
Second Dictionary
{'/Users/test/kodax-camera-M531.jpg': ['fcolor=2,74,6,20,30,1,2,0,1,0,0,0,1,3,2,0,0,0,0,0,1,1,1,0,0,2,0,0,0,2,2,0,0,0,0,0,2,2,1,0,0,5,0,0,0,1,4,0,0,0,0,0,2,2,1,0,0,1,0,0,0,3,1,0,0,0,0,0,1,1,0,0,0,3,0,0,0,1,2,0,0,0,0,0,2,2,1,0,0,4,0,0,0,0,5,0,0,0,0,0,2,1,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0', 'edge=1,4,1,88,128,22,8,39,25,142,230,226,31,60,64,255,252,12,76', 'texture=1,15,32,31,28,19,16,12,98']}
++++++++++++++++++
/Users/test/Transcend-8GB-Class-10-SDHC-Flash-Memory-Card.jpg
fcolor=2,4,14,5,0,0,0,0,0,0,0,0,0,0,12,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,6,0,0,0,0,1,0,0,0,0,0,0,0,0,0,20,9,0,0,0,2,2,0,0,0,0,0,0,0,0,0,13,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,10,8,0,0,0,1,2,0,0,0,0,0,0,0,0,0,17,17,0,0,0,3,6,0,0,0,0,0,0,0,0,0,7,5,0,0,0,2,0,0,0,0,0,0,0,0,0,0,4,3,0,0,0,1,1,0,0,0,0,0,0,0,0,0,6,6,0,0,0,2,3
fcolor=2,4,14,5,0,0,0,0,0,0,0,0,0,0,12,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,6,0,0,0,0,1,0,0,0,0,0,0,0,0,0,20,9,0,0,0,2,2,0,0,0,0,0,0,0,0,0,13,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,10,8,0,0,0,1,2,0,0,0,0,0,0,0,0,0,17,17,0,0,0,3,6,0,0,0,0,0,0,0,0,0,7,5,0,0,0,2,0,0,0,0,0,0,0,0,0,0,4,3,0,0,0,1,1,0,0,0,0,0,0,0,0,0,6,6,0,0,0,2,3
fcolor=2,74,6,20,30,1,2,0,1,0,0,0,1,3,2,0,0,0,0,0,1,1,1,0,0,2,0,0,0,2,2,0,0,0,0,0,2,2,1,0,0,5,0,0,0,1,4,0,0,0,0,0,2,2,1,0,0,1,0,0,0,3,1,0,0,0,0,0,1,1,0,0,0,3,0,0,0,1,2,0,0,0,0,0,2,2,1,0,0,4,0,0,0,0,5,0,0,0,0,0,2,1,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0
fcolor=2,4,14,5,0,0,0,0,0,0,0,0,0,0,12,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,6,0,0,0,0,1,0,0,0,0,0,0,0,0,0,20,9,0,0,0,2,2,0,0,0,0,0,0,0,0,0,13,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,10,8,0,0,0,1,2,0,0,0,0,0,0,0,0,0,17,17,0,0,0,3,6,0,0,0,0,0,0,0,0,0,7,5,0,0,0,2,0,0,0,0,0,0,0,0,0,0,4,3,0,0,0,1,1,0,0,0,0,0,0,0,0,0,6,6,0,0,0,2,3
edge=1,4,1,88,128,22,8,39,25,142,230,226,31,60,64,255,252,12,76
fcolor=2,4,14,5,0,0,0,0,0,0,0,0,0,0,12,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,6,0,0,0,0,1,0,0,0,0,0,0,0,0,0,20,9,0,0,0,2,2,0,0,0,0,0,0,0,0,0,13,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,10,8,0,0,0,1,2,0,0,0,0,0,0,0,0,0,17,17,0,0,0,3,6,0,0,0,0,0,0,0,0,0,7,5,0,0,0,2,0,0,0,0,0,0,0,0,0,0,4,3,0,0,0,1,1,0,0,0,0,0,0,0,0,0,6,6,0,0,0,2,3
texture=1,15,32,31,28,19,16,12,98
edge=1,252,1,32,124,194,63,252,67,15,240,1,7,244,66,47,0,192,63
edge=1,252,1,32,124,194,63,252,67,15,240,1,7,244,66,47,0,192,63
fcolor=2,74,6,20,30,1,2,0,1,0,0,0,1,3,2,0,0,0,0,0,1,1,1,0,0,2,0,0,0,2,2,0,0,0,0,0,2,2,1,0,0,5,0,0,0,1,4,0,0,0,0,0,2,2,1,0,0,1,0,0,0,3,1,0,0,0,0,0,1,1,0,0,0,3,0,0,0,1,2,0,0,0,0,0,2,2,1,0,0,4,0,0,0,0,5,0,0,0,0,0,2,1,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0
edge=1,252,1,32,124,194,63,252,67,15,240,1,7,244,66,47,0,192,63
edge=1,4,1,88,128,22,8,39,25,142,230,226,31,60,64,255,252,12,76
edge=1,252,1,32,124,194,63,252,67,15,240,1,7,244,66,47,0,192,63
texture=1,15,32,31,28,19,16,12,98
texture=1,78,27,37,13,6,6,7,78
texture=1,78,27,37,13,6,6,7,78
fcolor=2,74,6,20,30,1,2,0,1,0,0,0,1,3,2,0,0,0,0,0,1,1,1,0,0,2,0,0,0,2,2,0,0,0,0,0,2,2,1,0,0,5,0,0,0,1,4,0,0,0,0,0,2,2,1,0,0,1,0,0,0,3,1,0,0,0,0,0,1,1,0,0,0,3,0,0,0,1,2,0,0,0,0,0,2,2,1,0,0,4,0,0,0,0,5,0,0,0,0,0,2,1,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0
texture=1,78,27,37,13,6,6,7,78
edge=1,4,1,88,128,22,8,39,25,142,230,226,31,60,64,255,252,12,76
texture=1,78,27,37,13,6,6,7,78
texture=1,15,32,31,28,19,16,12,98
明らかにあなたが見ることができるように私は同じ価値の多くの繰り返しへの道を吐き出している
これらは私が扱っている実際の辞書です:
辞書1:
{'/Users/test/Transcend-8GB-Class-10-SDHC-Flash-Memory-Card.jpg': ['fcolor=2,4,14,5,0,0,0,0,0,0,0,0,0,0,12,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,6,0,0,0,0,1,0,0,0,0,0,0,0,0,0,20,9,0,0,0,2,2,0,0,0,0,0,0,0,0,0,13,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,10,8,0,0,0,1,2,0,0,0,0,0,0,0,0,0,17,17,0,0,0,3,6,0,0,0,0,0,0,0,0,0,7,5,0,0,0,2,0,0,0,0,0,0,0,0,0,0,4,3,0,0,0,1,1,0,0,0,0,0,0,0,0,0,6,6,0,0,0,2,3', 'edge=1,252,1,32,124,194,63,252,67,15,240,1,7,244,66,47,0,192,63', 'texture=1,78,27,37,13,6,6,7,78']}
辞書2:
{'/Users/test/kodax-camera-M531.jpg': ['fcolor=2,74,6,20,30,1,2,0,1,0,0,0,1,3,2,0,0,0,0,0,1,1,1,0,0,2,0,0,0,2,2,0,0,0,0,0,2,2,1,0,0,5,0,0,0,1,4,0,0,0,0,0,2,2,1,0,0,1,0,0,0,3,1,0,0,0,0,0,1,1,0,0,0,3,0,0,0,1,2,0,0,0,0,0,2,2,1,0,0,4,0,0,0,0,5,0,0,0,0,0,2,1,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0', 'edge=1,4,1,88,128,22,8,39,25,142,230,226,31,60,64,255,252,12,76', 'texture=1,15,32,31,28,19,16,12,98']}
ランバ機能があります
cosinLamba = lambda a, b : round(NP.inner(a, b)/(LA.norm(a)*LA.norm(b)), 3)
辞書1と辞書2を繰り返し処理して、dictionary1のfcolor値を取得したい 'fcolor=2,4,14,5,0,0,0,0,0,0,0,0,0,0,12,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,6,0,0,0,0,1,0,0,0,0,0,0,0,0,0,20,9,0,0,0,2,2,0,0,0,0,0,0,0,0,0,13,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,10,8,0,0,0,1,2,0,0,0,0,0,0,0,0,0,17,17,0,0,0,3,6,0,0,0,0,0,0,0,0,0,7,5,0,0,0,2,0,0,0,0,0,0,0,0,0,0,4,3,0,0,0,1,1,0,0,0,0,0,0,0,0,0,6,6,0,0,0,2,3'
およびdictionary2のfcolor値
'fcolor=2,74,6,20,30,1,2,0,1,0,0,0,1,3,2,0,0,0,0,0,1,1,1,0,0,2,0,0,0,2,2,0,0,0,0,0,2,2,1,0,0,5,0,0,0,1,4,0,0,0,0,0,2,2,1,0,0,1,0,0,0,3,1,0,0,0,0,0,1,1,0,0,0,3,0,0,0,1,2,0,0,0,0,0,2,2,1,0,0,4,0,0,0,0,5,0,0,0,0,0,2,1,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0'
それらをランバ関数に送信しますcosinLamba(valu1, value2)
。value1とvalue2は文字列であるため、これらを値として辞書に保存しました。そして、fcolor、texture、edgeに対して、各辞書の特定の画像に保存したすべてのベクトルを実行したいと思います。