Sep-02-2020, 11:29 AM
Dear All the following svm script, gives the error (raise IOError("Cannot understand given URI: %s." % uri_r),
Would you please to show me where is my mistake,
Would you please to show me where is my mistake,
# import all the required modules
from skimage.io import imread
from pathlib import Path
from sklearn.model_selection import train_test_split, GridSearchCV
import numpy as np
import numpy
from sklearn import svm, metrics
def ReadImage(filepath, dimension=(500, 581)):
"""
Load and read stacked-image file
Parameters
----------
container_path : string or unicode
Path to the main folder holding one category
dimension : tuple
size to which image are adjusted to
Returns
-------
np.arry of stacked image
"""
img = imread(filepath)
return np.array(img)
def SplitData(file):
img = imread(file)
imge = []
target = []
for r, c in img:
imge.append(X_train)
target.append(y_train)
X_train, X_test, y_train, y_test = train_test_split(imge,
target,
test_size=.25,
random_state=123)
return SplitData
def ReshapeImage(X_train, y_train):
nsamples, nx, ny = X_train.shape
dx_train_dataset = X_train.reshape((nsamples,nx*ny))
nsamples, nx, ny = y_train.shape
dy_train_dataset = y_train.reshape((nsamples,nx*ny))
return ReshapeImage
def Classifier(clf, param_grid):
svc = svm.SVC()
param_grid = [
{'C': [1, 10, 100, 1000], 'kernel': ['linear']},
{'C': [1, 10, 100, 1000], 'gamma': [0.001, 0.0001], 'kernel': ['rbf']},
]
clf = GridSearchCV(svc, param_grid)
clf.fit(dx_train_dataset, dy_train_dataset)
y_pred = Classifier.predict(X_test)
print ("Accuracy: %s" % Classifier.score(X_test, y_test))
print("Classification report for - \n{}:\n{}\n".format(
clf, metrics.classification_report(y_test, y_pred)))
return Classifier
stacked_img = ReadImage('D:\MyProject\preprocessing\stacked_data\data_stacked.tif'
,dimension=(500, 581))
spd = SplitData(stacked_img)