tf.image.sample_distorted_bounding_box ValueError

匿名 (未验证) 提交于 2019-12-03 01:27:01

问题:

I am trying to augment existing labeled bounding boxed image for making more object detection training data using the function tf.image.sample_distorted_bounding_box but I keep getting these errors found here. I'm pretty sure my bounding box is set correctly because it works when I draw the bounding box.

img = mpimg.imread('bPawn0.jpg') img = img.reshape(1,300,300,3) boxes = [100,88,253,209] box = np.ones([1,1,4]) for i in range(4):     box[:,:,i] = boxes[i]/300 box = tf.convert_to_tensor(box, np.float32)  begin, size, bbox_for_draw = tf.image.sample_distorted_bounding_box(tf.shape(img),bounding_boxes=box)  ValueError: Tried to convert 'min_object_covered' to a tensor and failed. Error: None values not supported. 

Any suggestions as to what I am doing wrong here?

回答1:

I'm wondering if this is a bug in the sample_distorted_bounding_box() code, since I don't see a test that doesn't specify that argument to the function explicitly.

Can you try setting that argument explicitly, something like this?

sample_distorted_bounding_box = tf.image.sample_distorted_bounding_box(     tf.shape(image),     bounding_boxes=bbox,     min_object_covered=0.1,     aspect_ratio_range=[0.75, 1.33],     area_range=[0.05, 1.0],     max_attempts=100,     use_image_if_no_bounding_boxes=True) 

https://github.com/tensorflow/models/blob/master/research/inception/inception/image_processing.py#L235



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