Hi, When I run sim_grasp_multiple.py and add the parameter --vis for simulation grasping, the following problem occurred:

(giga) wang@wang-U:~/github/GIGA$ python scripts/sim_grasp_multiple.py --num-view 1 --object-set pile/test --scene pile --num-rounds 100 --sideview --add-noise dex --force --best --model /home/wang/github/GIGA/data/models/giga_pile.pt --type giga --result-path /home/wang/github/GIGA/data/result --vis

pybullet build time: May 28 2020 16:37:34 Loading [giga] model from /home/wang/github/GIGA/data/models/giga_pile.pt 0%| | 0/100 [00:00<?, ?it/s] Traceback (most recent call last): File "scripts/sim_grasp_multiple.py", line 123, in main(args) File "scripts/sim_grasp_multiple.py", line 38, in main success_rate, declutter_rate = clutter_removal.run( File "/home/wang/github/GIGA/src/vgn/experiments/clutter_removal.py", line 89, in run logger.log_mesh(scene_mesh, visual_mesh, f'round_{round_id:03d}trial{trial_id:03d}') File "/home/wang/github/GIGA/src/vgn/experiments/clutter_removal.py", line 177, in log_mesh aff_mesh.export(self.mesh_dir / (name + "_aff.obj")) File "/home/wang/anaconda3/envs/giga/lib/python3.8/site-packages/trimesh/scene/scene.py", line 842, in export return export.export_scene( File "/home/wang/anaconda3/envs/giga/lib/python3.8/site-packages/trimesh/exchange/export.py", line 210, in export_scene raise ValueError('file_type not specified!') ValueError: file_type not specified!

What is the reason? Thank you！ ^_^

Hi,thank you for you repo! However, I encountered an error when running sim_grasp_multiple.py. As shown in the figure

Could you give me some suggestions？

What is the coordinate system / reference you take for adding the grasp visual in grasp2mesh()?

I tweaked your code a bit to run it on my dataset, but the gripper is way farther from the object mesh. I ran the pre-trained model and got the best grasp params (affordance, rotation, width and center). Here is the code I used to visualize:

# Loading custom data mesh
mesh = trimesh.load('mydata/processed/meshes/map_{}.obj'.format(scene_id),force='scene')
grasp = Grasp(Transform(ori, pos, width)

finger_depth = 0.05
color = np.array([0, 250, 0, 180]).astype(np.uint8)
radius = 0.1 * finger_depth
w, d = grasp.width, finger_depth
pose = grasp.pose * Transform(Rotation.identity(), [0.0, -w / 2, d / 2])
scale = [radius, radius, d]
left_finger = trimesh.creation.cylinder(radius,
                                        d,
                                        transform=pose.as_matrix())
scene.add_geometry(left_finger, 'left_finger')

# right finger
pose = grasp.pose * Transform(Rotation.identity(), [0.0, w / 2, d / 2])
scale = [radius, radius, d]
right_finger = trimesh.creation.cylinder(radius,
                                            d,
                                            transform=pose.as_matrix())
scene.add_geometry(right_finger, 'right_finger')

# wrist
pose = grasp.pose * Transform(Rotation.identity(), [0.0, 0.0, -d / 4])
scale = [radius, radius, d / 2]
wrist = trimesh.creation.cylinder(radius,
                                    d / 2,
                                    transform=pose.as_matrix())
scene.add_geometry(wrist, 'wrist')

# palm
pose = grasp.pose * Transform(
    Rotation.from_rotvec(np.pi / 2 * np.r_[1.0, 0.0, 0.0]),
    [0.0, 0.0, 0.0])
scale = [radius, radius, w]
palm = trimesh.creation.cylinder(radius, w, transform=pose.as_matrix())
scene.add_geometry(palm, 'palm')
scene.add_geometry(trimesh.creation.axis())

Hi all, I ran python scripts/save_occ_data_parallel.py /path/to/raw/data 100000 2 --num-proc 40 to generate occupancy data with the pre-generated data provided by you. I found this line in python scripts/save_occ_data_parallel.py encounter *** AttributeError: 'str' object has no attribute 'copy'. The environmental setting is aligned with the description in README.md

Just wonder whether there is any solution for this issue. Any help appreciated :)

I have tried to install the program in wsl2 using ubuntu. If I use command "nvidia-smi' in linux, I can get a result:

But when I try to install cuda from nvidia by wget https://developer.download.nvidia.com/compute/cuda/11.5.0/local_installers/cuda_11.5.0_495.29.05_linux.run sudo sh cuda_11.5.0_495.29.05_linux.run It will warn like that:

Thus is it necessary to download and install the nvidia driver for linux 64-bit in nvidia website? I tried to do that, but I can not install it locally in wsl2-ubuntu system. It reminded that there is not an NVIDIA GPU in this system. Thanks!

Hi，

The results I got with the model you gave are different from those in your paper, and the results are different under different devices. I want to know if you have the same problem at that time. Is this because the test objects are randomly selected and randomly placed? Is the test scene generated each time not fixed, so sometimes the experimental results are different？

Looking forward to your answer. Thank you！

By naively following the installation instructions, I'm finding that this line hangs when running with multiprocessing, but not when running in the main thread.

Would it be possible to list the full conda environment you used, by running conda list -e > requirements.txt? For example, I would be interested to know which versions of python, Open3D and multiprocessing you used.

Any help appreciated :)

Hello! I just began my robotics research which is very related to yours' . I am trying to follow your work in Github. When I carried out the step 4 of Installation, firstly it said the cl.exe could not be found, so I installed Visual Studio 2017 and set the path of environment variables, like following: env variable "path": env variable "LIB": env variable "INCLUDE":

But an error still occurred: LINK : fatal error LNK1181: can not open input file“m.lib” . The specific output in the command line:

I thought it might still caused by libpath or something, but I could not fix it after trials. I think it will definitely affect the following steps of installation or data generation so it is annoying. Do you have some ideas or suggestions to fix it? Thanks a lot!

Hi @Steve-Tod , I have two questions:

1. how to query at a higher resolution of 60x60x60? (I have tried directly set the resolution as 60 in the detection_implicit.py, but qual_vol[valid_voxels == False] = 0.0 gives me an error that the size of valid voxels doesn't match the size of qual_vol)
2. Without sideview, the performances decrease a lot. Do you have any explanations?

Thanks!

Hi,I training one epoch on pile scene,and estimated time to spend more than 10 hours.

Here is my computer configuration： pytorch 1.7.0 py3.8_cuda10.2.89_cudnn7.6.5_0 GPU:GeForce RTX 2070SUPER CPU:Intel(R) Core(TM) i7-9700 CPU @ 3.00GHz Memory:16G Hard Disk Drive:1T HDD

Here are some screenshots:

I found that GPU utilization was erratic and was 0 for a long time, and CPU utilization was not very high. So I presume it's because the io speed of the HDD hard disk drive is too slow.

I hope you can help me find the problem, thanks!

It would be very useful to have the training data returned from generate_data_parallel.py script available to download, for both the pile and packed cases.

I appreciate this may be a large amount of memory, and therefore difficult to host, so there is no expectation of course! But it would avoid people needing to run the costly data generation process locally in order to experiment with the training.

hi, when i run the command: python scripts/construct_dataset_parallel.py --num-proc 40 --single-view --add-noise dex /path/to/raw/data /path/to/new/data An error like this: and i change the num-proc into 1 An error like this:

1. Why process "pos" in dataset like the line:

https://github.com/UT-Austin-RPL/GIGA/blob/d67c4388d334babe6c11c1555a6e848fb4828c84/src/vgn/dataset_voxel.py#L35

2. Why the "self.size" in

https://github.com/UT-Austin-RPL/GIGA/blob/d67c4388d334babe6c11c1555a6e848fb4828c84/src/vgn/simulation.py#L37

define like this?

3. Why the do not use "pos" in " x, y, z" instead of "i, j k" in following lines? https://github.com/UT-Austin-RPL/GIGA/blob/d67c4388d334babe6c11c1555a6e848fb4828c84/scripts/construct_dataset_parallel.py#L73