ValueError : Tensor conversion requested dtype int32 for Tensor with dtype float32 while using tf. Image .crop_to_bounding_box… here is a solution to the problem.
ValueError : Tensor conversion requested dtype int32 for Tensor with dtype float32 while using tf. Image .crop_to_bounding_box
I’m trying to crop an image based on a bounding box.
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)
I get the following error:
ValueError: Tensor conversion requested dtype int32 for Tensor with dtype
float32: 'Tensor("Const_7:0", shape=(), dtype=float32)'
Const_7:0 is ymin
Thanks for any help on how to fix this
Solution
TensorFlow uses tf.slice to crop the image, which requires tensor total_height
, The data types for total_width
, ymin
, and xmin
are 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)