我试图根据边界框裁剪图像。
bbox = [{'width': '500', 'ymin': '125', 'depth': '3', 'xmax': '387', 'xmin': '29', 'height': '375', 'ymax': '245'}]
ymin = float(bbox['ymin'])/float(bbox['height'])
ymax = float(bbox['ymax'])/float(bbox['height'])
xmin = float(bbox['xmin'])/float(bbox['width'])
xmax = float(bbox['xmax'])/float(bbox['width'])
total_height = tf.convert_to_tensor(ymax_int - ymin_int)
total_width = tf.convert_to_tensor(xmax - xmin)
ymin = tf.convert_to_tensor(ymin)
xmin = tf.convert_to_tensor(xmin)
img=mpimg.imread(filename)
img = tf.convert_to_tensor(img)
image = tf.image.crop_to_bounding_box(img, ymin, xmin, total_height, total_width)
我收到以下错误:
ValueError: Tensor conversion requested dtype int32 for Tensor with dtype
float32: 'Tensor("Const_7:0", shape=(), dtype=float32)'
Const_7:0 is ymin
任何有关如何解决此问题的帮助表示赞赏
最佳答案
TensorFlow使用tf.slice裁剪图像,这要求张量total_height
,total_width
,ymin
和xmin
的数据类型为int32
:
total_height = tf.convert_to_tensor(ymax_int - ymin_int, dtype=tf.int32)
total_width = tf.convert_to_tensor(xmax - xmin, dtype=tf.int32)
ymin = tf.convert_to_tensor(ymin, dtype=tf.int32)
xmin = tf.convert_to_tensor(xmin, dtype=tf.int32)