def refresh_dataTrain(request): # label, directory = get_Dataset('data_train') lbp, label, directory = get_lbpDataset('data_train', 8, 4) # local = get_lbpDataset('data_train', 8, 4) # print(local) DB.delete_all('tb_fastDataTraining') for x in range(len(label)): # # file_name = os.path.join("/home/night/Documents/Python3/TA_Wasis/myWebsite/",directory[x]) string = "" for z in lbp[x]: if string == "": string = str(z) else: string += "," + str(z) data_tabel = { 'lbp': string, 'label': label[x], 'directory': directory[x], # 'file_name' : file_name, } DB.insert('tb_fastDataTraining', data_tabel) return redirect('fast_train')
def index(request): label, directory = get_Dataset('data_train') # local = get_lbpDataset('data_train', 8, 4) # print(local) DB.delete_all('tb_dataTraining') for x in range(len(label)): # file_name = os.path.join("/home/night/Documents/Python3/TA_Wasis/myWebsite/",directory[x]) # string = "" # for z in data[x]: # if string == "": # string = str(z) # else: # string += ","+str(z) data_tabel = { # 'lbp' : string, 'label': label[x], 'directory': directory[x], # 'file_name' : file_name, } DB.insert('tb_dataTraining', data_tabel) tb_dataTraining = DB.find('tb_dataTraining') # data_train[0][0] # for data in data_train: # for dt in data: # print(dt) # print("\n") # print(data[0]) # print(data['label']) # print(data['directory']) # print("\n") context = { 'Judul': 'Dataset', 'SubJudul': 'Berikut dataset yang akan digunakan sebagai data training k-NN', 'tb_dataTraining': tb_dataTraining # 'data' : data, # 'label': label, # 'directory':directory } return render(request, 'Data_Train/index.html', context)