Shape Error in Tensorflow

So I have some 32×32 images with 3 color channels so I flattened them out and made their shape 3072. I loaded the images and reshaped them to be a (1, 3072) numpy matrix but when the network is running it will give the following error:

Traceback (most recent call last):
  File "/Users/Me/project/lib/python3.4/site-packages/tensorflow/python/client/session.py", line 428, in _do_run
target_list)
tensorflow.python.pywrap_tensorflow.StatusNotOK: Invalid argument: Incompatible shapes: [300] vs. [100]       
[[Node: Equal_1 = Equal[T=DT_INT64,   _device="/job:localhost/replica:0/task:0/cpu:0"](ArgMax_2, ArgMax_3)]]

This is the code that loads the images:

    name = QtGui.QFileDialog.getOpenFileNames(self, 'Open File')
    fname = [str(each) for each in name]
    flist = []
    dlist = []
    for n, val in enumerate(name):
        flist.append(val)
        img = Image.open(flist[n])
        img.load()
        data = np.asarray(img, dtype = "int32")
        print(data.shape)
        data.shape = (1, 3072)
        quack = np.asmatrix(data)
        print(quack)
        dlist.append(quack)
    print(dlist)
    for n in range(len(dlist)):
        if n==0:
            self.inlist = dlist[n]
        if n>0:
            self.inlist = np.vstack((self.inlist, dlist[n]))

I am doing it in batches of 100.

Shape Error in Tensorflow