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I tried to train a simple model with your code, but unfortunately I get the following error when I try to train:
InvalidArgumentError (see above for traceback): assertion failed: [] [Condition x == y did not hold element-wise:] [x (mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/Shape_1:0) = ] [4 16] [y (mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/strided_slice:0) = ] [1 64]
[[Node: mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/assert_equal/Assert/Assert = Assert[T=[DT_STRING, DT_STRING, DT_STRING, DT_INT32, DT_STRING, DT_INT32], summarize=3, _device="/job:localhost/replica:0/task:0/device:CPU:0"](mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/assert_equal/All/_4229, mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/assert_equal/Assert/Assert/data_0, mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/assert_equal/Assert/Assert/data_1, mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/assert_equal/Assert/Assert/data_2, mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/Shape/_4231, mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/assert_equal/Assert/Assert/data_4, mrcnn_class_loss/SparseSoftmaxCrossEntropyWithLogits/strided_slice/_4233)]]
As I see the problem is with the tensor shapes, so it can happen that there is a problem with my dataset.
When I call dataset.load_image(...) it returns an image with shape (128, 128, 3)
When I call dataset.load_bbox(...) it returns a list of bounding boxes with shape: (nb_of_bboxes, 4) and a list of class ids to the corresponding bboxes
I hope you encountered with the same problem and can help me with this.
The text was updated successfully, but these errors were encountered:
Instead of pooled = tf.expand_dims(pooled, 0) the right output is pooled = tf.reshape(pooled, (self.batch_size, self.num_rois, self.channel_num)) as your comment says that the returned tensor should have a shape of (batch, num_rois, class_num)
I tried to train a simple model with your code, but unfortunately I get the following error when I try to train:
As I see the problem is with the tensor shapes, so it can happen that there is a problem with my dataset.
dataset.load_image(...)
it returns an image with shape(128, 128, 3)
dataset.load_bbox(...)
it returns a list of bounding boxes with shape:(nb_of_bboxes, 4)
and a list of class ids to the corresponding bboxesI hope you encountered with the same problem and can help me with this.
The text was updated successfully, but these errors were encountered: