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Python FileManager.csvToArray方法代碼示例

本文整理匯總了Python中FileManager.FileManager.csvToArray方法的典型用法代碼示例。如果您正苦於以下問題:Python FileManager.csvToArray方法的具體用法?Python FileManager.csvToArray怎麽用?Python FileManager.csvToArray使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在FileManager.FileManager的用法示例。


在下文中一共展示了FileManager.csvToArray方法的5個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: creaFileFeatures

# 需要導入模塊: from FileManager import FileManager [as 別名]
# 或者: from FileManager.FileManager import csvToArray [as 別名]
	def creaFileFeatures(self,key=None):

		if key == None:
			## PREPROCESSING PERCORSI IMMAGINI
			fm = FileManager()
			file_positive = self.root+self.keywords+"/"+self.keywords+"_" + self.detector + "_" + self.extractor + ".csv"

			# Creo una lista contenente tutte le immagini (jpg) positive (Filtro estension)
			listArrayPositive = fm.listNoHiddenFiles(self.root+self.keywords,self.estension)

			## SAVE FEATURES IN FILES
			# Controllo se e' gia' presente, altrimenti leggo il file e restituisco array
			if not os.path.isfile(file_positive):
				print "Nuovo File Features Positive " + self.detector + " + " + self.extractor + " creato."
				X_positive = []
				for k in range(0,len(listArrayPositive)): # Da eliminare file csv ed altri
					base_name = self.root+self.keywords+"/"+self.keywords+fm.correggi(k)+ self.estension
					print "Immagini " + str(k) + " -> " + base_name 
					ret = (self.obj.elabora(base_name)) #[0:cut_features]
					X_positive.append(ret)

				fm.arrayToCsv(X_positive,file_positive)
			else:
				print "File Features Positive " + self.detector + " + " + self.extractor + " esiste gia."
				X_positive = fm.csvToArray(file_positive)
		else:
			## PREPROCESSING PERCORSI IMMAGINI
			fm = FileManager()
			file_positive = self.root+key+"/"+key+"_" + self.detector + "_" + self.extractor + ".csv"

			# Creo una lista contenente tutte le immagini (jpg) positive (Filtro estension)
			listArrayPositive = fm.listNoHiddenFiles(self.root+key,self.estension)

			## SAVE FEATURES IN FILES
			# Controllo se e' gia' presente, altrimenti leggo il file e restituisco array
			if not os.path.isfile(file_positive):
				print "Nuovo File Features Positive " + self.detector + " + " + self.extractor + " creato."
				X_positive = []
				for k in range(0,len(listArrayPositive)): # Da eliminare file csv ed altri
					base_name = self.root+key+"/"+key+fm.correggi(k)+ self.estension
					print "Immagini " + str(k) + " -> " + base_name 
					ret = (self.obj.elabora(base_name)) #[0:cut_features]
					X_positive.append(ret)

				fm.arrayToCsv(X_positive,file_positive)
			else:
				print "File Features Positive " + self.detector + " + " + self.extractor + " esiste gia."
				X_positive = fm.csvToArray(file_positive)

		return X_positive
開發者ID:massi92,項目名稱:DIP-Project_MGFF,代碼行數:52,代碼來源:FeaturesFile.py

示例2: negativeFeaturesSingleCat

# 需要導入模塊: from FileManager import FileManager [as 別名]
# 或者: from FileManager.FileManager import csvToArray [as 別名]
	def negativeFeaturesSingleCat(self,category):
		## PREPROCESSING PERCORSI IMMAGINI
		fm = FileManager()

		X_negative = []
		#for i in range(0,len(listDir)):
		file_negative = self.root+category+"/"+category+"_" + self.detector + "_" + self.extractor + ".csv"
		if not os.path.isfile(file_negative):
			self.creaFileFeatures(category)
		else:
			X = fm.csvToArray(file_negative)
			X_negative = X_negative + X
		return X_negative		
開發者ID:massi92,項目名稱:DIP-Project_MGFF,代碼行數:15,代碼來源:FeaturesFile.py

示例3: featuresCategories

# 需要導入模塊: from FileManager import FileManager [as 別名]
# 或者: from FileManager.FileManager import csvToArray [as 別名]
	def featuresCategories(self):
		#recupera tutte le categorie, senza distinzione fra positive e negative
		#usando un numero incrementale per l'assegnazione delle categorie
		fm = FileManager()
		X_train = []
		y_train = []
		assoc = dict()
		listCategories = fm.listNoHiddenDir(self.root)
		index = 1
		for cat in listCategories:
			file_positive = self.root+cat+"/"+cat+"_" + self.detector + "_" + self.extractor + ".csv"
			X_cat = fm.csvToArray(file_positive)
			X_train = X_train + X_cat
			y_train = y_train + [index]*len(X_cat)
			assoc[cat] = index
			index = index + 1

		return X_train,y_train,assoc
開發者ID:massi92,項目名稱:DIP-Project_MGFF,代碼行數:20,代碼來源:FeaturesFile.py

示例4: negativeFeatures

# 需要導入模塊: from FileManager import FileManager [as 別名]
# 或者: from FileManager.FileManager import csvToArray [as 別名]
	def negativeFeatures(self):
		## PREPROCESSING PERCORSI IMMAGINI
		fm = FileManager()
		#file_negative = self.root+self.keywords+"/"+self.keywords+"_" + self.detector + "_" + self.extractor + "_negative.csv"

		# List dir contiene tutte le cartelle della root img
		listDir = fm.listNoHiddenDir(self.root)

		# Cerco l'indice della cartella della Keywords
		indexKeywords = listDir.index(self.keywords)
		# Vado ad eliminare nella lista cartelle quella della keywords
		listDir.pop(indexKeywords)

		X_negative = []
		for i in range(0,len(listDir)):
			file_negative = self.root+listDir[i]+"/"+listDir[i]+"_" + self.detector + "_" + self.extractor + ".csv"
			if not os.path.isfile(file_negative):
				self.creaFileFeatures(listDir[i])
			else:
				X = fm.csvToArray(file_negative)
				X_negative = X_negative + X
		return X_negative
開發者ID:massi92,項目名稱:DIP-Project_MGFF,代碼行數:24,代碼來源:FeaturesFile.py

示例5: str

# 需要導入模塊: from FileManager import FileManager [as 別名]
# 或者: from FileManager.FileManager import csvToArray [as 別名]
			print "Immagini " + str(k) + " -> " + base_name 
			ret = (obj.elabora(base_name)) #[0:cut_features]
			X_negative.append(ret)

	fm.arrayToCsv(X_negative,file_negative)
else:
	print "File Features Negative " + detector + " + " + extractor + " esiste gia."


#raw_input()


## FEATURES ML FROM FILES
# Array dai file csv
print "Caricamento file csv into array"
X_positive_from_csv = fm.csvToArray(file_positive)
X_negative_from_csv = fm.csvToArray(file_negative)

X_total = X_positive_from_csv + X_negative_from_csv
y_total = [0]*len(X_positive_from_csv)+[1]*len(X_negative_from_csv)

#print y_total

# Preparing cross_validation
#X_train, X_test, y_train, y_test = cross_validation.train_test_split(X_total, y_total, test_size=0.3, random_state=1)
X_train = X_total
y_train = y_total
X_test = [obj.elabora("./gatto.jpg")]
y_test = [1]

# ML
開發者ID:massi92,項目名稱:DIP-Project_MGFF,代碼行數:33,代碼來源:provaFeatures.py


注:本文中的FileManager.FileManager.csvToArray方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台,相關代碼片段篩選自各路編程大神貢獻的開源項目,源碼版權歸原作者所有,傳播和使用請參考對應項目的License;未經允許,請勿轉載。