Mask_RCNN
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Differences in results for this model on TF2.0CPU and TF2.7 GPU
Hi,
I ran this model on a custom dataset TF2.0 CPU and TF2.7GPU. Got good results on test data for object detection on TF2.0 but TF2.7 GPU results are totally bad. Not a single object was identified after same number of epochs. Is it because MRCNN model is not ported to TF2.7 as yet.
Meet the same problem, tf2.5 in my local laptop works fine but colab use tf2.8 which generates totally random results.
agree!I used tf2.8 to run this project,but some errors emerged like "ValueError: Tried to convert 'shape' to a tensor and failed. Error: None values not supported" .
Since TF 2.5 there are several tf.compat.v1 cuts providing very strange training and inference results, indeed. I refactored the model and the DataGenerator so it can be fully used in any TF 2 environment (tested on TF 2.9.1 docker). Check out the repo.