GmdMiss_Folder = os.path.join(os.getcwd(), '..', 'Photo', 'GMD Miss')
GmdMiss_List = os.listdir(GmdMiss_Folder)for i in range(0, len(GmdMiss_List)):
Img = os.path.join(os.getcwd(), GmdMiss_Folder, GmdMiss_List[i])
Img = cv2.imread(Img, cv2.IMREAD_GRAYSCALE)
Img = np.array(Img)
Img = cv2.resize(Img, dsize=(1920, 1080), interpolation=cv2.INTER_AREA)
Img_Miss_List.append(Img)
i=0
while True:
Img = Img_Miss_List[i]
with tf.Session() as sess:
graph = tf.Graph()
with graph.as_default():
with tf.name_scope("Convolution"):
Img = Convolution(Img)
i += 1
...
The codes below are omitted
...def Convolution(img):
kernel = tf.Variable(tf.truncated_normal(shape=[180, 180, 3, 3], stddev=0.1))
img = img.astype('float32')
img = tf.nn.conv2d(np.expand_dims(img, 0), kernel, strides=[ 1, 15, 15, 1], padding='VALID')
return img错误是.。
ValueError:形状必须为4级,但对于输入形状为1,1080,1920,180,180,3,3的“卷积/卷积2D”(op:“Conv2D”),则为3级。
发布于 2019-11-03 08:59:20
您的conv2D内核[filter_height, filter_width, in_channels, out_channels]期望输入图像有3个通道,它是一个具有[batch, in_height, in_width, in_channels]形状的4D张量,而您则以灰度格式加载输入图像。因此,您需要加载具有三个通道的彩色图像:
Img = cv2.imread(Img) # By default cv2 load image in BGR format
Img = cv2.cvtColor(Img, cv2.COLOR_BGR2RGB) # convert BGR to RGB format希望能帮上忙。
https://stackoverflow.com/questions/58677984
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