Hi I am new to open Cv and Python :) I try to run my script with python 2.7 and 2.4.13 openCV my script:
****************
-- coding: utf-8 --
import cv2 import numpy as np import os import sys from scipy.cluster.vq import *
def get_all_files_dir(path): return [os.path.join(path, file) for file in os.listdir(path)]
class StatModel(object): def load(self, fn): self.model.load(fn) def save(self, fn): self.model.save(fn)
class SVM(StatModel): def __init__(self): self.model = cv2.SVM()
def train(self, samples, responses,cParam):
params = dict( kernel_type = cv2.SVM_LINEAR,
svm_type = cv2.SVM_C_SVC
,C = cParam )
self.model.train(samples, responses, params = params)
def predict(self, samples):
return np.float32( [self.model.predict(sample) for sample in samples])
def predictImages(inputPath,outputPath):
Path = inputPath
tst_descriptors = []
image_paths_test =get_all_files_dir(Path)
for image_path in image_paths_test:
image = cv2.imread(image_path)
keypoints = featureDetector.detect(image)
keypoints, descriptor = descriptorExtractor.compute(image, keypoints)
tst_descriptors.append((image_path, descriptor))
descriptors = tst_descriptors[0][1]
for image_path, descriptor in tst_descriptors[0:]:
descriptors = np.vstack((descriptors, descriptor))
test_features = np.zeros((len(image_paths_test), k), "float32")
for i in xrange(len(image_paths_test)):
print i
print vocab == None
print tst_descriptors[i][1] == None
#print len(tst_descriptors)
#print tst_descriptors[i][1].shape
#print vocab.shape
words, distance = vq(tst_descriptors[i][1],vocab)
for word in words:
test_features[i][word] += 1
#normalize
test_features[i] = test_features[i] = test_features[i]/ np.linalg.norm(test_features[i])
predictions = [classes_names[int(cls)] for cls in clf.predict(test_features)]
with open(outputPath+"\ClassOutput.txt","w") as text_file:
text_file.writelines(img + " : " + cls + "\n" for img,cls in zip(image_paths, predictions))
if len(sys.argv) != 4: print("Run the script as follows: python CV2.py <trainingimagespath> <testimagespath> <textoutputpath>") print("TrainingImagesPath should have two folders inside, one with positive examples and one with negative examples") print("I.E. Face and NotFace - same naming as the classes") sys.exit()
training_folder_path = sys.argv[1] test_input_path = sys.argv[2] outputPath = sys.argv[3] classes_names = os.listdir(training_folder_path)
matcher = cv2.DescriptorMatcher_create("FlannBased") featureDetector = cv2.FeatureDetector_create("SIFT") descriptorExtractor = cv2.DescriptorExtractor_create("SIFT")
image_paths = [] image_classes = [] class_id = 0 for training_name in classes_names: dir = os.path.join(training_folder_path, training_name) class_path = get_all_files_dir(dir) image_paths+=class_path image_classes+=[class_id]*len(class_path) class_id+=1
listOfDescriptors = [] for image_path in image_paths: image = cv2.imread(image_path) keypoints = featureDetector.detect(image) keypoints, descriptor = descriptorExtractor.compute(image, keypoints) listOfDescriptors.append((image_path, descriptor))
descriptors = listOfDescriptors[0][1] for image_path, descriptor in listOfDescriptors[1:]: descriptors = np.vstack((descriptors, descriptor))
K-Means
k = 80 vocab, variance = kmeans(descriptors, k, 1)
Histograms
image_features = np.zeros((len(image_paths), k), "float32") for i in xrange(len(image_paths)): words, distance = vq(listOfDescriptors[i][1],vocab) for word in words: image_features[i][word] += 1 #normalize image_features[i] = image_features[i]/ np.linalg.norm(image_features[i])
clf = SVM() clf.train(image_features, np.array(image_classes),4)
predictImages(test_input_path,outputPath)
print("Done. Check input directory for text file.")
*****************
I run the script like this: python CV2.py <trainingimagespath> <testimagespath> <textoutputpath>
and I got the error :
n [1]: runfile('C:/Users/hilalham/Desktop/cv/CV2/CV2.py', args='C:/Users/hilalham/Desktop/cv/CV2/trainImg C:/Users/hilalham/Desktop/cv/CV2/testImg C:/Users/hilalham/Desktop/cv/CV2/output.txt', wdir='C:/Users/hilalham/Desktop/cv/CV2')
0
False
True
C:/Users/hilalham/Desktop/cv/CV2/CV2.py:55: FutureWarning: comparison to None will result in an elementwise object comparison in the future.
print vocab == None
Traceback (most recent call last):
File "<ipython-input-1-a2fc42f81ed6>", line 1, in <module> runfile('C:/Users/hilalham/Desktop/cv/CV2/CV2.py', args='C:/Users/hilalham/Desktop/cv/CV2/trainImg C:/Users/hilalham/Desktop/cv/CV2/testImg C:/Users/hilalham/Desktop/cv/CV2/output.txt', wdir='C:/Users/hilalham/Desktop/cv/CV2')
File "C:\Users\hilalham\AppData\Local\Continuum\Anaconda2\lib\site-packages\spyder\utils\site\sitecustomize.py", line 866, in runfile execfile(filename, namespace)
File "C:\Users\hilalham\AppData\Local\Continuum\Anaconda2\lib\site-packages\spyder\utils\site\sitecustomize.py", line 87, in execfile exec(compile(scripttext, filename, 'exec'), glob, loc)
File "C:/Users/hilalham/Desktop/cv/CV2/CV2.py", line 128, in <module> predictImages(test_input_path,outputPath)
File "C:/Users/hilalham/Desktop/cv/CV2/CV2.py", line 61, in predictImages words, distance = vq(tst_descriptors[i][1],vocab)
File "C:\Users\hilalham\AppData\Local\Continuum\Anaconda2\lib\site-packages\scipy\cluster\vq.py", line 210, in vq obs = _asarray_validated(obs, check_finite=check_finite)
File "C:\Users\hilalham\AppData\Local\Continuum\Anaconda2\lib\site-packages\scipy_lib_util.py", line 231, in _asarray_validated raise ValueError('object arrays are not supported')
ValueError: object arrays are not supported
any one who can help, please?
