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We could not automatically infer the shape of the Lambda's output. Please specify the output_shape
argument for this Lambda layer.
#3038
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Same problem here, which appears in the line I am running Traceback (most recent call last): We could not automatically infer the shape of the Lambda's output. Please specify the Arguments received by Lambda.call(): |
Hello I was able to run it in colab. I also encountered the same errors. It was very difficult. https://github.com/z-mahmud22/Mask-RCNN_TF2.14.0 I used the repo here. |
still not solved |
Hello @zlao3118 zlao3188 Which versions do you use? tensorflow==2.5.0 keras==2.3.1 python 3.8.0 Have you tried? |
I was able to solve it with python 3.11 and tensorflow 2.12.0 |
|
Hi! I solved it by defining those 🟢 Change this :
for this:
🟢 change this:
for this:
🟢 and this: |
Thank you very much for your help! And I would like to ask what version of Tensorflow you are using?
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主题: Re: [matterport/Mask_RCNN] We could not automatically infer the shape of the Lambda's output. Please specify the `output_shape` argument for this Lambda layer. (Issue #3038)
Hi! I solved it by defining those output_shape parameters in my model.py file on functions that use Lambda layer.
But as recommended above, it is better to update Tensorflow because other related errors will appear throughout the execution of the model.
🟢 Change this :
gt_boxes = KL.Lambda(lambda x: norm_boxes_graph( x, K.shape(input_image)[1:3]))(input_gt_boxes)
for this:
gt_boxes = KL.Lambda(lambda x: norm_boxes_graph( x, K.shape(input_image)[1:3]), output_shape=(None, 4))(input_gt_boxes)
🟢 change this:
active_class_ids = KL.Lambda( lambda x: parse_image_meta_graph(x)["active_class_ids"] )(input_image_meta)
for this:
active_class_ids = KL.Lambda( lambda x: parse_image_meta_graph(x)["active_class_ids"], output_shape=(None,))(input_image_meta)
🟢 and this:
output_rois = KL.Lambda(lambda x: x * 1, name="output_rois")(rois)
for this:
output_rois = KL.Lambda(lambda x: x * 1, output_shape=(None, 4), name="output_rois")(rois)
in model.py file
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Probably a 1.* too. I also have to update Tensorflow and keep fighting to get Mask working in a week 🫠🙃 |
Traceback (most recent call last):
File "D:\Mask_RCNN-2.1\Mask_RCNN-2.1\samples\balloon\balloon.py", line 332, in
model = modellib.MaskRCNN(mode="inference", config=config,
File "D:\Mask_RCNN-2.1\Mask_RCNN-2.1\samples\balloon\model.py", line 1768, in init
self.keras_model = self.build(mode=mode, config=config)
File "D:\Mask_RCNN-2.1\Mask_RCNN-2.1\samples\balloon\model.py", line 1950, in build
fpn_classifier_graph(rpn_rois, mrcnn_feature_maps, config.IMAGE_SHAPE,
File "D:\Mask_RCNN-2.1\Mask_RCNN-2.1\samples\balloon\model.py", line 916, in fpn_classifier_graph
shared = KL.Lambda(lambda x: K.squeeze(K.squeeze(x, 3), 2),
File "D:\python310\lib\site-packages\keras\src\utils\traceback_utils.py", line 122, in error_handler
raise e.with_traceback(filtered_tb) from None
File "D:\python310\lib\site-packages\keras\src\layers\core\lambda_layer.py", line 95, in compute_output_shape
raise NotImplementedError(
NotImplementedError: Exception encountered when calling Lambda.call().
We could not automatically infer the shape of the Lambda's output. Please specify the
output_shape
argument for this Lambda layer.Arguments received by Lambda.call():
• args=('<KerasTensor shape=(None, 1000, 1, 1, 1024), dtype=float32, sparse=False, name=keras_tensor_428>',)
• kwargs={'mask': 'None'}
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