def create_labels(count, hog_list, total_data, batch_size):
#labels are one-hot vectors. But 0 is replaced with -1
point = count
path = hog_list[count][0]
lab = hog_list[count][1]
y = np.zeros([1, num_classes])
y[0][lab] = 1
x = hog.read_hog_file(path)
x = np.expand_dims(x, axis=0)
count += 1
extra = np.min([batch_size, total_data - point])
while count < point + extra and count < total_data:
path = hog_list[count][0]
lab = hog_list[count][1]
y_new = np.zeros([1, num_classes])
y_new[0][lab] = 1
y = np.concatenate((y, y_new), axis=0)
x_new = hog.read_hog_file(path)
x_new = np.expand_dims(x_new, axis=0)
x = np.concatenate((x, x_new), axis=0)
count += 1
return x, y
def create_svm_labels(count, hog_list, total_data, batch_size, class_num, key):
point = count
path = hog_list[count][0]
lab = hog_list[count][1]
y = np.array([[key]])
if lab == class_num:
y[0][0] = 1
x = hog.read_hog_file(path)
x = np.expand_dims(x, axis=0)
count += 1
extra = np.min([batch_size, total_data - point])
while count < point + extra and count < total_data:
path = hog_list[count][0]
lab = hog_list[count][1]
y_new = np.array([[key]])
if lab == class_num:
y_new[0][0] = 1
y = np.concatenate((y, y_new), axis=0)
x_new = hog.read_hog_file(path)
x_new = np.expand_dims(x_new, axis=0)
x = np.concatenate((x, x_new), axis=0)
count += 1
return x, y
def create_labels(count, hog_list, total_data, batch_size):
point = count
path = hog_list[count][0]
lab = hog_list[count][1]
y = np.zeros([1, num_classes])
y[0][lab] = 1
#print("Extracting HOG features from image...."+str(len(train_list)-count-1)+' more images left.....')
x = hog.read_hog_file(path)
x = np.expand_dims(x, axis=0)
count += 1
extra = np.min([batch_size, total_data - point])
while count < point + extra and count < total_data:
path = hog_list[count][0]
lab = hog_list[count][1]
y_new = np.zeros([1, num_classes])
y_new[0][lab] = 1
y = np.concatenate((y, y_new), axis=0)
#print("Extracting HOG features from image...."+str(len(train_list)-count-1)+' more images left.....')
x_new = hog.read_hog_file(path)
x_new = np.expand_dims(x_new, axis=0)
x = np.concatenate((x, x_new), axis=0)
count += 1
return x, y
