simaoh
commented
7 years ago I can load the model from this Checkpoint (https://github.com/CharlesShang/FastMaskRCNN/issues/86#issuecomment-309022377), and get predictions from it. However, I can only get predictions for an output_tensor before the ROIAlign layer, but not for any tensor in the graph after that layer. Example:
# this works
output_tensor = graph.get_tensor_by_name("pyramid_1/ROIAlign_2/Crop:0")
# this doesn't work
output_tensor = graph.get_tensor_by_name("pyramid_1/ROIAlign_2/Reshape_2:0")There's a bug in the ROIAlign layer with the py_func used to generate anchors.
- My understanding is that the py_fun is not stored in the graph and cannot be reconstructed.
- Or is this bug related to casting anchor coordinates to ints?
- Can anyone here (@amirbar, @sairin1202 , @hari-sikchi , @Cangrc , @mariolew , @cuihuitao) try to load the graph this way, and reproduce the error / find a workaround ?
tf.reset_default_graph()
checkpoint_dir = "/my/directory/for/segmentation/FastMaskRCNN/output/mask_rcnn/500k/"
meta_file_path = checkpoint_dir + "coco_resnet50_model.ckpt-499999.meta"
ckpt_file_path = checkpoint_dir + "coco_resnet50_model.ckpt-499999"
# load graph
saver = tf.train.import_meta_graph(meta_file_path, clear_devices=True)
graph = tf.get_default_graph()
# initialize and load weights
sess = tf.Session()
sess.run(tf.global_variables_initializer())
saver.restore(sess, ckpt_file_path)
# Input images
input_tensor = graph.get_tensor_by_name("Reshape_2:0")
output_tensor = graph.get_tensor_by_name("pyramid_2/MaskEncoder/Reshape_2:0")
# Mask output
results = sess.run(
[output_tensor],
#[tf.reduce_mean(input_tensor)],
feed_dict={input_tensor:images}
)
y-dep
how to test data ??