python - TypeError: float() argument must be a string or a number, not 'NoneType' Error by Machine Learning code of Sentdex

Question

I tried to work with sentdex tutorial "Building the Network - Using Convolutional Neural Network to Identify Dogs vs Cats" and got the error: "TypeError: float() argument must be a string or a number, not 'NoneType'". I don't know why, because I just changed the location where I import the Images from the harddrive to the google drive cloud. My Code:

from google.colab import drive
drive.mount('/content/drive')

import cv2
import numpy as np
import os
from random import shuffle
from tqdm import tqdm

TRAIN_DIR = '/content/drive/MyDrive/Facharbeit/train'
TEST_DIR = '/content/drive/MyDrive/Facharbeit/test'
IMG_SIZE = 50
LR = 1e-3

MODEL_NAME = 'dogsvscats-{}-{}.model'.format(LR, '2conv-basic')

def label_img(img):
  word_label = str(img.split('.')[-3])
  if word_label == 'c': return [1,0]
  elif word_label == 'd':return [0,1]

def create_train_data():
    training_data = []
    for img in tqdm(os.listdir(TRAIN_DIR)):
        label = label_img(img)
        path = os.path.join(TRAIN_DIR,img)
        img = cv2.imread(path,cv2.IMREAD_GRAYSCALE)
        img = cv2.resize(img, (IMG_SIZE,IMG_SIZE))
        training_data.append([np.array(img),np.array(label)])
    shuffle(training_data)
    np.save('train_data.npy', training_data)
    return training_data

def process_test_data():
    testing_data = []
    for img in tqdm(os.listdir(TEST_DIR)):
        path = os.path.join(TEST_DIR,img)
        img_num = img.split('.')[0]
        img = cv2.imread(path,cv2.IMREAD_GRAYSCALE)
        img = cv2.resize(img, (IMG_SIZE,IMG_SIZE))
        testing_data.append([np.array(img), img_num])
        
    shuffle(testing_data)
    np.save('test_data.npy', testing_data)
    return testing_data

import tflearn
from tflearn.layers.conv import conv_2d, max_pool_2d
from tflearn.layers.core import input_data, dropout, fully_connected
from tflearn.layers.estimator import regression

convnet = input_data(shape=[None, IMG_SIZE, IMG_SIZE, 1], name='input')

convnet = conv_2d(convnet, 32, 5, activation='relu')
convnet = max_pool_2d(convnet, 5)

convnet = conv_2d(convnet, 64, 5, activation='relu')
convnet = max_pool_2d(convnet, 5)

convnet = fully_connected(convnet, 1024, activation='relu')
convnet = dropout(convnet, 0.8)

convnet = fully_connected(convnet, 2, activation='softmax')
convnet = regression(convnet, optimizer='adam', learning_rate=LR, loss='categorical_crossentropy', name='targets')

model = tflearn.DNN(convnet, tensorboard_dir='log')

if os.path.exists('{}.meta'.format(MODEL_NAME)):
    model.load(MODEL_NAME)
    print('model loaded!')

train = train_data[:-500]
test = train_data[-500:]

model.fit({'input': X}, {'targets': Y}, n_epoch=3, validation_set=({'input': test_x}, {'targets': test_y}), snapshot_step=500, show_metric=True, run_id=MODEL_NAME)

When running the code I got the error message:

Run id: dogsvscats-0.001-2conv-basic.model
Log directory: log/
---------------------------------
Training samples: 73500
Validation samples: 1500
--
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-33-489069081a3c> in <module>()
      1 model.fit({'input': X}, {'targets': Y}, n_epoch=3, validation_set=({'input': test_x}, {'targets': test_y}), 
----> 2     snapshot_step='500', show_metric=True, run_id=MODEL_NAME)

5 frames
/usr/local/lib/python3.6/dist-packages/tflearn/models/dnn.py in fit(self, X_inputs, Y_targets, n_epoch, validation_set, show_metric, batch_size, shuffle, snapshot_epoch, snapshot_step, excl_trainops, validation_batch_size, run_id, callbacks)
    204                          excl_trainops=excl_trainops,
    205                          run_id=run_id,
--> 206                          callbacks=callbacks)
    207 
    208     def retrieve_data_preprocessing_and_augmentation(self):

/usr/local/lib/python3.6/dist-packages/tflearn/helpers/trainer.py in fit(self, feed_dicts, n_epoch, val_feed_dicts, show_metric, snapshot_step, snapshot_epoch, shuffle_all, dprep_dict, daug_dict, excl_trainops, run_id, callbacks)
    342                                                        (bool(self.best_checkpoint_path) | snapshot_epoch),
    343                                                        snapshot_step,
--> 344                                                        show_metric)
    345 
    346                             # Update training state

/usr/local/lib/python3.6/dist-packages/tflearn/helpers/trainer.py in _train(self, training_step, snapshot_epoch, snapshot_step, show_metric)
    826         tflearn.is_training(True, session=self.session)
    827         _, train_summ_str = self.session.run([self.train, self.summ_op],
--> 828                                              feed_batch)
    829 
    830         # Retrieve loss value from summary string

/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    966     try:
    967       result = self._run(None, fetches, feed_dict, options_ptr,
--> 968                          run_metadata_ptr)
    969       if run_metadata:
    970         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1158             feed_handles[subfeed_t.ref()] = subfeed_val
   1159           else:
-> 1160             np_val = np.asarray(subfeed_val, dtype=subfeed_dtype)
   1161 
   1162           if (not is_tensor_handle_feed and

/usr/local/lib/python3.6/dist-packages/numpy/core/_asarray.py in asarray(a, dtype, order)
     81 
     82     """
---> 83     return array(a, dtype, copy=False, order=order)
     84 
     85 

TypeError: float() argument must be a string or a number, not 'NoneType'

Could somebody help me, I really don't know the mistake I made? I would be very thankful!

Answer 1

等待大神答复