ValueError異常：無效的文字在tensorflow INT（）基數爲10

我試圖在tensorflow與圖像玩，我試圖運行此代碼，但它給這個錯誤：ValueError異常：無效的文字在tensorflow INT（）基數爲10

/anaconda/bin/python "/Users/tony/Downloads/Tensorflow learning/9th pro.py" 
/anaconda/lib/python3.5/site-packages/matplotlib/tight_layout.py:222: UserWarning: tight_layout : falling back to Agg renderer 
    warnings.warn("tight_layout : falling back to Agg renderer") 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. 
Traceback (most recent call last): 
    File "/Users/tony/Downloads/Tensorflow learning/9th pro.py", line 11, in <module> 
    sess_1=sess.run(slice_thing,feed_dict={place_holder1:image_a}) 
    File "/anaconda/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 767, in run 
    run_metadata_ptr) 
    File "/anaconda/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 938, in _run 
    np_val = np.asarray(subfeed_val, dtype=subfeed_dtype) 
    File "/anaconda/lib/python3.5/site-packages/numpy/core/numeric.py", line 531, in asarray 
    return array(a, dtype, copy=False, order=order) 
ValueError: invalid literal for int() with base 10: 'dd.jpg'

我的代碼是：

import skimage.io as i 
import matplotlib.pyplot as plt 
import tensorflow as tf 

image_a="dd.jpg" 
read_image=i.imread(image_a) 
show_image=i.imshow(image_a) 
place_holder1=tf.placeholder("uint8",[None,None,3]) 
slice_thing=tf.slice(place_holder1,[1,1,0],[1,1,0]) 
with tf.Session() as sess: 
    sess_1=sess.run(slice_thing,feed_dict={place_holder1:image_a}) 
    print(sess_1.shape) 
print(i.imshow(sess_1)) 
plt.show()

如果我試圖用浮動更換INT：

place_holder1=tf.placeholder("float32",[None,None,3])

然後我收到此錯誤：

ValueError: could not convert string to float: 'dd.jpg'

我的第二個問題是什麼是3在這一行

place_holder1=tf.placeholder("unit8",[None,None,3])

如果我沒有學到那麼無，無=行，列

placeholder("unit8",[row,col,3]

我瞭解它的約束矩陣大小

但這裏3是什麼？

來源

2017-04-22 stephen

你place_holder1是大小無，無，3和浮點型（tf.placeholder("float32",[None,None,3])）的張量。而不是傳遞一個字符串，它是文件的名稱。閱讀這個文件並將其轉換爲張量。

你3是通道（顏色）的數目。對於RGB圖像是3

來源

2017-04-22 09:12:10

你能解釋一下多一點我的意思是[無，無，3意味着它的3×3的矩陣？因爲一個球場是None，第二個是None，那麼第三個會是3？ – stephen

@stephen沒有，沒有，3'不是一個矩陣，這是一個等級3的張量。你可以把它想象成3個大小爲'none，none'的矩陣。「無」意味着任何維度，因此它可以是「5,7,3」或「1,4,3」。我建議你閱讀介紹性教程，因爲這些是基本的定義，沒有這些基本的定義就不可能在TF中做任何事情 –

你說過：「你可以把它想象成3個大小都不是的矩陣，但是如果我寫[None，None，3 ]，則第一個無是張量的深度，第2個無是該張量中的矩陣行，第3個是這些矩陣的列。所以它將是「無約束矩陣深度無約束的行，每個矩陣只有3列」。？ – stephen

ValueError異常：無效的文字在tensorflow INT（）基數爲10

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