sjingjia / planerectr Goto Github PK

Hello, I found self.losses contains ['labels', 'masks', 'plane_depths', 'params', 'Q', 'plane_depths'], I don't understand the meaning of loss_Q. Did the paper mention this loss? Thanks for your effort.

I went through the code but I am still confused if there are anything more needed than segmented and depth image to generate .ply file. Also, can you mention where to input my own segmented and depth image instead of the one generated by your network?

@SJingjia

Cannot Inference on these pretrained models: PlaneRecTR_swinb_pretrained.pth & PlaneRecTR_hrnet32_pretrained.pth

Traceback (most recent call last):
  File "/workspace/hardik/PlaneRecTR/demo/demo.py", line 211, in <module>
    predictions = demo.run_on_image(img)
                  ^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/hardik/PlaneRecTR/demo/predictor.py", line 54, in run_on_image
    predictions = self.predictor(image)
                  ^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/hardik/PlaneRecTR/detectron2/detectron2/engine/defaults.py", line 319, in __call__
    predictions = self.model([inputs])[0]
                  ^^^^^^^^^^^^^^^^^^^^
  File "/root/anaconda3/envs/planerectr/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/anaconda3/envs/planerectr/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/hardik/PlaneRecTR/demo/../PlaneRecTR/PlaneRecTR_model.py", line 299, in forward
    plane_seg, inferred_planes_depth, inferred_seg_depth, valid_param = retry_if_cuda_oom(self.plane_inference)(mask_cls_result, mask_pred_result, param_pred_result, depth_pred_result)
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/hardik/PlaneRecTR/detectron2/detectron2/utils/memory.py", line 70, in wrapped
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/hardik/PlaneRecTR/demo/../PlaneRecTR/PlaneRecTR_model.py", line 367, in plane_inference
    inferred_seg_depth = (segmentation * valid_depth_pred).sum(0) # [h, w]
                          ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~
RuntimeError: The size of tensor a (256) must match the size of tensor b (1088) at non-singleton dimension 2

Hi, Thank you for the great work. Would you please share the inference script of PlaneRecTR? I would like to test your work on my own image. Thanks!

Hi, thanks for the good work. When I downloaded tfrecords data from PlaneNet, and then ran the commands to convert it to npz data and generate json files required by detectron2, I met the following error. How can I solve it? Thanks!

...
...
18899
18999
19099
19199
19299
Traceback (most recent call last):
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call
return fn(*args)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn
target_list, run_metadata)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.OutOfRangeError: FIFOQueue '_2_batch/fifo_queue' is closed and has insufficient elements (requested 1, current size 0)
[[{{node batch}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "data_tools/convert_tfrecords.py", line 59, in
img, gt_dict = sess.run([img_inp_train, global_gt_dict_train])
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 956, in run
run_metadata_ptr)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1180, in _run
feed_dict_tensor, options, run_metadata)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
run_metadata)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: FIFOQueue '_2_batch/fifo_queue' is closed and has insufficient elements (requested 1, current size 0)
[[node batch (defined at /home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]

Original stack trace for 'batch':
File "data_tools/convert_tfrecords.py", line 46, in
img_inp_train, global_gt_dict_train, local_gt_dict_train = reader_train.getBatch(filename_queue_train, batchSize=1, getLocal=True)
File "/home/zlq/code/PlaneRecTR/PlanarReconstruction/data_tools/RecordReaderAll.py", line 62, in getBatch
tf.train.batch([image, planes, depth, normal, semantics, segmentation, boundary, numPlanes, features['image_path'], features['info']], batch_size=batchSize, capacity=(NUM_THREADS + 2) * batchSize, num_threads=1)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 324, in new_func
return func(*args, **kwargs)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/training/input.py", line 1020, in batch
name=name)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/training/input.py", line 789, in _batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/ops/data_flow_ops.py", line 489, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/ops/gen_data_flow_ops.py", line 3862, in queue_dequeue_many_v2
timeout_ms=timeout_ms, name=name)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
op_def=op_def)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
attrs, op_def, compute_device)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
op_def=op_def)
File "/home/zlq/anaconda3/envs/planerectr/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 1748, in init
self._traceback = tf_stack.extract_stack()