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