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:  vs.  [[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.