Question

所以我正在研究一个手写识别项目，并且使用IamDB可以正常工作。但是，当我尝试自己拍摄手写照片时，出现此错误，您知道如何解决吗？我尝试将图片更改为灰度，但不起作用

images = []
PTH = Path_to_test 
#filename  = os.path.basename(PTH[0])
filename = PTH[0]
#******************************************************
print (filename)
im = Image.open(filename)
#print ("cu")
cur_width = im.size[0]
cur_height = im.size[1]
    # print(cur_width, cur_height)

height_fac = 113 / cur_height

new_width = int(cur_width * height_fac)
size = new_width, 113

imresize = im.resize((size), Image.ANTIALIAS)  # Resize so height = 113 while keeping aspect ratio
now_width = imresize.size[0]
now_height = imresize.size[1]
    # Generate crops of size 113x113 from this resized image and keep random 10% of crops

avail_x_points = list(range(0, now_width - 113 ))# total x start points are from 0 to width -113

    # Pick random x%
factor = 0.1 
pick_num = int(len(avail_x_points)*factor)

random_startx = sample(avail_x_points,  pick_num)

for start in random_startx:
  imcrop = imresize.crop((start, 0, start+113, 113))
  images.append(np.asarray(imcrop))
T_test = np.array(images)
print (T_test.shape)
T_test = T_test.reshape(T_test.shape[0], 113, 113, 1)
    #convert to float and normalize
T_test = T_test.astype('float32')
T_test /= 255
shuffle(T_test)  
print (T_test.shape)

T_test的形状是（3，113，113，3），它是手写的黑白照片。这是错误：

     34 T_test = np.array(images)
     35 print (T_test.shape)
---> 36 T_test = T_test.reshape(T_test.shape[0], 113, 113, 1)
     37     #convert to float and normalize
     38 T_test = T_test.astype('float32')

ValueError：无法将大小为114921的数组重塑为形状（3,113,113,1）我也使用

predictions = model.predict(T_test, verbose =1)

所以我无法将其更改为（T_test.shape [0]，113、113、3）

Answer 1

图像有3个通道，因此您需要使用3个而不是1个。

T_test = T_test.reshape(T_test.shape[0], 113, 113, 3)

为什么当我np.array（图像）时出现重塑错误

1 个答案: