def edge():
edgeFeats = EdgeHistogramFeatureExtractor()
a = np.array(edgeFeats.extract(watchman.imgbank[0]))
if len(watchman.imgbank) > 1:
b = np.array(edgeFeats.extract(watchman.imgbank[1]))
else:
b = np.array(edgeFeats.extract(watchman.imgbank[0]))
AandB = np.sum(np.square((a-b)))
return AandB
def feature_extractor():
#Abrir arquivo que vai receber as features dos arquivos de imagens
file = "image_features_train_20_10_1_Novo.arff"
text_file = open(file, "a")
trainPath = "C:/Python27/ARP/Dataset/train2"
dirList = os.listdir(trainPath)
edge = EdgeHistogramFeatureExtractor(20)
for dirName in dirList:
fileList = os.listdir(trainPath + '/' + dirName)
maxsize = len(fileList)
for i in range(0, maxsize):
#print fileList[i]
filePATH = (trainPath + '/' + dirName + '/' + fileList[i])
img = Image(filePATH)
#Feature - Edge histogram
edge_vecs = edge.extract(img)
edge_fields = edge.getFieldNames()
for y in range(0, edge.getNumFields()):
#print edge_fields[y], '=', edge_vecs[y]
text_file.write(str(edge_vecs[y]) + ",")
#Feature - Hue
hue = HueHistogramFeatureExtractor(10)
hue_vecs = hue.extract(img)
hue_fields = hue.getFieldNames()
for i in range(0, hue.getNumFields()):
# #print hue_fields[i], '=', hue_vecs[i]
text_file.write(str(hue_vecs[i]) + ",")
Morph1 = MorphologyFeatureExtractor()
Morph2 = Morph1.extract(img)
text_file.write(str(Morph2) + ",")
text_file.write(dirName + "\n")
text_file.close()
def extract_edges(image, data, slices):
edgeExtractor = EdgeHistogramFeatureExtractor(bins=4)
image_bins = split_image_into_slices(image, slices)
data["edge-angles"] = []
data["edge-lengths"] = []
for image_bin in image_bins:
edge_angles_and_lengths = edgeExtractor.extract(image_bin)
data["edge-angles"] += edge_angles_and_lengths[: len(edge_angles_and_lengths) / 2]
data["edge-lengths"] += edge_angles_and_lengths[len(edge_angles_and_lengths) / 2 :]
return data
def EHDFeatures(image):
"""
Function that calculate the edge histogram of an image.
Coded by An Li
"""
img1 = Image(image)
edgeFeats = EdgeHistogramFeatureExtractor(bins=16)
results = np.array(edgeFeats.extract(img1), dtype=np.float32)
return results
