zju3dv / clean-pvnet Goto Github PK

hello,

I followed the steps and now trying to test the model with the command:
python run.py --type evaluate --cfg_file configs/linemod.yaml model cat

But I got an error as :
ModuleNotFoundError: No module named 'lib.csrc.ransac_voting.ransac_voting'

As I have already setup the 'ransac_voting' with no error. Can I get any advice about why is this happening?

I am following the project structure and the custom.yaml file, I would like to load the pre trained model myself. Before loading the model, I would need to instantiate the class like this below:

model = TheModelClass(*args, **kwargs)

According to the custom.yaml file; the 'task' is pvnet, but the network is res.
clean-pvnet/lib/networks/pvnet

Which class network would the appropriate one to use when loading the custom model in pytorch?

Would it be this one: Resnet18?
https://github.com/zju3dv/clean-pvnet/blob/07e7c09e80cde938e013d8bc2880605add33a0ce/lib/networks/pvnet/resnet18.py

Or this one: PoseResNet?
https://github.com/zju3dv/clean-pvnet/blob/07e7c09e80cde938e013d8bc2880605add33a0ce/lib/networks/resnet.py

My end goal is to just take my pretrained model that I trained; and create a brand new inference code pipeline, where I can customize it with my own usecase.

Thank you, your document is very useful to me.

I want to use your network through my webcam.

Can I get a webcam demo?

Hello

There is an error in your code.

Traceback (most recent call last):
attrs = DatasetCatalog.dataset_attrs[name]
KeyError: 'CustomTrain'

https://github.com/zju3dv/clean-pvnet/blob/master/lib/datasets/dataset_catalog.py#L74

The corresponding code is missing.
'CustomTrain': {
'id': 'linemod',
'data_root': 'data/custom',
'ann_file': 'data/custom/train.json',
'split': 'train'
},

my command is = python train_net.py --cfg_file configs/linemod.yaml train.dataset CustomTrain test.dataset CustomTrain model tless_06 train.batch_size 8 eval_ep 20 train.epoch 201

Traceback (most recent call last):
File "train_net.py", line 67, in
main()
File "train_net.py", line 63, in main
train(cfg, network) # @ go line 28
File "train_net.py", line 37, in train
trainer.train(epoch, train_loader, optimizer, recorder) # Go to train --> lib - train - trainers - trainer.py
File "/home/hwanglab/PycharmProjects/clean-pvnet/lib/train/trainers/trainer.py", line 33, in train
for iteration, batch in enumerate(data_loader): # get Datasets from lib - datasets - tless_train - pvnet.py - def getitem
File "/home/hwanglab/anaconda3/envs/pvnet/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 582, in next
return self._process_next_batch(batch)
File "/home/hwanglab/anaconda3/envs/pvnet/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 608, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
TypeError: Traceback (most recent call last):
File "/home/hwanglab/anaconda3/envs/pvnet/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 99, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/home/hwanglab/anaconda3/envs/pvnet/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 99, in
samples = collate_fn([dataset[i] for i in batch_indices])
File "lib/datasets/linemod/pvnet.py", line 41, in getitem
index, height, width = index_tuple
TypeError: 'int' object is not iterable

i'm having trouble using custom data.
I'd appreciate it if you could look at the code once.

thank you

david

When I set up the python environment, I have this error:

I saw a video which shows a cat with a hat. I want to learn how to do that, so is it possible to release the code? If you can i will be very appreciated. Thanks your help.

Hello @pengsida ,
is it possible to infer on linemod dataset with pretrained tless weights?

Regards,
Mahesh kashyap.

I am getting the error below, but I have double checked and the cuda-9.0 does exist in the specified usr/local directory. I am following the exact setup directions as listed on a Ubuntu machine 16.04

No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda-9.0'
/usr/local/cuda-9.0
Traceback (most recent call last):
File "setup.py", line 64, in
ext_modules=get_extensions(),
File "setup.py", line 41, in get_extensions
raise NotImplementedError('Cuda is not availabel')
NotImplementedError: Cuda is not availabel

Thank you so much for sharing the code and model for tless.
While training tless dataset, i am facing this error. Could you please help me with this?

Traceback (most recent call last):
File "train_net.py", line 57, in
main()
File "train_net.py", line 53, in main
train(cfg, network)
File "train_net.py", line 35, in train
trainer.val(epoch, val_loader, evaluator, recorder)
File "/datasets/Mahesh_kashyap/pvnet-clean/clean-pvnet/lib/train/trainers/trainer.py", line 82, in val
output, loss, loss_stats, image_stats = self.network(batch)
File "/home/belakavadi/anaconda3/envs/pvnet/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/home/belakavadi/anaconda3/envs/pvnet/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 152, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/home/belakavadi/anaconda3/envs/pvnet/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 162, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/home/belakavadi/anaconda3/envs/pvnet/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 83, in parallel_apply
raise output
File "/home/belakavadi/anaconda3/envs/pvnet/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 59, in _worker
output = module(*input, **kwargs)
File "/home/belakavadi/anaconda3/envs/pvnet/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "lib/train/trainers/pvnet.py", line 24, in forward
weight = batch['mask'][:, None].float()
KeyError: 'mask'

Regards,
Mahesh

Hi! I'm currently training the network on the prepared Tless dataset and have a question about the renderings.

As I've understood it you add renderings to the training data as well which can be found in /data/tless/renders. I noticed however that there are no renderings for some of the objects in the dataset. Is this correct or have I failed a step where they were supposed to be added?

After I modified the fps.txt file, I did train.

However, the fps.txt file was modified automatically.

Am I correct in that you are not using rendered data for the training here, specifically in training custom dataset?

If you did not use rendered data, did it reproduce paper results on LINEMOD and related datasets?

Every 5:th epoch, training using command python train_net.py --cfg_file configs/tless/tless_01.yaml gets interrupted with RuntimeError from the ransac_voting_gpu.py file. Have you experienced this before? Do you know why it happens every fifth epoch?

eta: 0:00:18 epoch: 9 step: 4980 vote_loss: 0.0147 seg_loss: 0.0149 loss: 0.0296 data: 0.2134 batch: 0.5426 lr: 0.001000 max_mem: 2463
eta: 0:00:00 epoch: 9 step: 4999 vote_loss: 0.0141 seg_loss: 0.0147 loss: 0.0288 data: 0.2152 batch: 0.5443 lr: 0.001000 max_mem: 2463
eta: 0:00:00 epoch: 9 step: 5000 vote_loss: 0.0141 seg_loss: 0.0147 loss: 0.0289 data: 0.2197 batch: 0.5473 lr: 0.001000 max_mem: 2463
0%| | 0/2927 [00:00<?, ?it/s]
Traceback (most recent call last):
File "train_net.py", line 58, in
main()
File "train_net.py", line 54, in main
train(cfg, network)
File "train_net.py", line 35, in train
trainer.val(epoch, val_loader, evaluator, recorder)
File "/home/franswed/Documents/MastersThesis2020/clean-pvnet-master/lib/train/trainers/trainer.py", line 82, in val
output, loss, loss_stats, image_stats = self.network.module(batch)
File "/home/franswed/anaconda3/envs/pvnet2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "lib/train/trainers/pvnet.py", line 16, in forward
output = self.net(batch['inp'])
File "/home/franswed/anaconda3/envs/pvnet2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "lib/networks/pvnet/resnet18.py", line 94, in forward
self.decode_keypoint(ret)
File "lib/networks/pvnet/resnet18.py", line 69, in decode_keypoint
kpt_2d = ransac_voting_layer_v3(mask, vertex, 128, inlier_thresh=0.99, max_num=100)
File "/home/franswed/Documents/MastersThesis2020/clean-pvnet-master/lib/csrc/ransac_voting/ransac_voting_gpu.py", line 190, in ransac_voting_layer_v3
ATA=torch.matmul(normal.permute(0,2,1),normal) # [vn,2,2]
RuntimeError: cublas runtime error : the GPU program failed to execute at /pytorch/aten/src/THC/THCBlas.cu:450

Thank you for your wonderful results and code sharing.

Currently, I want to proceed customer learning using tless dataset.
I saw the file t-less_01.yaml in your configs folder.

Therefore, I would like to ask you how you constructed the pose ground truth.
If you have sample ground truth for Tless 01, I would appreciate it if you could share it with me.

P.S I created a pose ground truth using the value of the gt.yml file given in the tless dataset. Is this the right way?

I'll wait for your reply.

Thank you.

sorry to bother you , when i run the command python run.py --type evaluate --cfg_file configs/linemod.yaml model cat test.icp True, i come across the following error " Error in `python': free(): invalid pointer: 0x000055e1deea4028 *** Aborted (core dumped)", and i find the "evaluator = imp.load_source(module, path).Evaluator(cfg.result_dir)" code cause the problem. Can you help me, very thanks.

when I compiled "cd ../nn python setup.py build_ext --inplace",I met some problems".
1.gcc: error: /usr/local/cuda-9.0/lib64/libcudart.so: No such file or directory
So, I found my cuda is 10.0.130, and I change <setup.py>-cuda 9.0 to cuda 10.0.
Then, I met the problem2 again

2.In file included from tmpxft_00001f84_00000000-4_nearest_neighborhood.cudafe1.stub.c:1:0:
/tmp/tmpxft_00001f84_00000000-4_nearest_neighborhood.cudafe1.stub.c: In function ‘void __device_stub__Z27findNearestPoint3DIdxKernelPfS_Piiiii(float*, float*, int*, int, int, int, int)’:
/tmp/tmpxft_00001f84_00000000-4_nearest_neighborhood.cudafe1.stub.c:11:153: error: ‘__args_arr’ was not declared in this scope
_par1, int __par2, int __par3, int __par4, int __par5, int __par6){__cudaSetup
^
/tmp/tmpxft_00001f84_00000000-4_nearest_neighborhood.cudafe1.stub.c:11:164: error: ‘__args_idx’ was not declared in this scope
__par2, int __par3, int __par4, int __par5, int __par6){_cudaSetupArgSimple(
^
In file included from tmpxft_00001f84_00000000-4_nearest_neighborhood.cudafe1.stub.c:1:0:
/tmp/tmpxft_00001f84_00000000-4_nearest_neighborhood.cudafe1.stub.c: In function ‘void __device_stub__Z27findNearestPoint2DIdxKernelPfS_Piiiii(float, float, int*, int, int, int, int)’:
/tmp/tmpxft_00001f84_00000000-4_nearest_neighborhood.cudafe1.stub.c:1:162: error: ‘__args_arr’ was not declared in this scope
/tmp/tmpxft_00001f84_00000000-4_nearest_neighborhood.cudafe1.stub.c:1:173: error: ‘__args_idx’ was not declared in this scope
generating ./_ext.c
(already up-to-date)
the current directory is '/home/yang/clean-pvnet-master/lib/csrc/nn'
running build_ext
building '_ext' extension
gcc -pthread -B /home/yang/anaconda3/envs/pvnet/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/yang/anaconda3/envs/pvnet/include/python3.6m -c _ext.c -o ./_ext.o
gcc -pthread -shared -B /home/yang/anaconda3/envs/pvnet/compiler_compat -L/home/yang/anaconda3/envs/pvnet/lib -Wl,-rpath=/home/yang/anaconda3/envs/pvnet/lib -Wl,--no-as-needed -Wl,--sysroot=/ ./_ext.o src/nearest_neighborhood.cu.o /usr/local/cuda-10.0/lib64/libcudart.so -lstdc++ -o ./_ext.cpython-36m-x86_64-linux-gnu.so

Must I use cuda9.0?

Can you list all hardware requirements please?

What is GPU memory size?
and others...

Hello,

I would like to create a brand new custom dataset to test without the aruco markers around the object to understand generalization. I have been going through the code, and it seems like the custom.yaml file and the dataset catalog are the necessary files where I have to add / change.

I am also assuming for visualization / evaluation only inference is being done on a pre - trained model with a simple RGB image as the input.

After creating this dataset, and adding it to the dataset catalog, what details should I be aware of. For example do I need an ann file or a value for 'split'? Is is fine to assume that inference on a pretrained model would only require a RGB image?

Also, why does the inference line in these 2 functions differ?

def run_evaluate():
.......
output = network(inp)

def run_visualize():
.........
output = network(batch['inp'], batch)

Thank you for sharing your amazing research.

I wonder how you got the Diameter of the Linemod dataset you saved in advance.

If you have a code, I'd appreciate it if you could share it.

cheers

David

Hi,
Is there a problem with the link to the truncation dataset? I can download others but can't download this one. Thank you~

Hi,

thank you for your great work!

I noticed that here you suggested a few modifications to be done to the code to make it work in a multi-object setting.

I am interested in training a single network with samples containing multiple objects (with different class), can you give me a few hints about which parts of the network architecture should be modified to adapt it to this case?

Hi,
From what I have observed from the code, every class has separate models, which seems contradicting to the paper. Can you please explain this if I have understood correctly?

Why there is separate model for each class instead of 1 model ?

Assuming there are C classes of objects and K keypoints for each class, PVNet takes as input the H × W × 3 image, processes it with a fully convolutional architecture, and outputs the H ×W ×(K ×2×C) tensor representing unit vectors and H×W ×(C+1) tensor representing class probabilities.

Moreover, for LineMOD ver_dim is taken as 18. Should it not be 8*2 = 16, for K = 8 key points.

Thnaks.

What does the diameter.txt means ? Is that the custom object's size? Thank your help

Can i ask how many gpus and what kind do you use in this new project?
And, how much time did it cost?
Thanks

你好，我执行这一步python run.py --type evaluate --cfg_file configs/linemod.yaml model cat test.icp True，出现OpenGL.error.NullFunctionError: Attempt to call an undefined function glCreateTextures, check for bool(glCreateTextures) before calling
这个是怎么回事?在网上搜了些方法试了也没好。麻烦你看看。

I have run an inference on an object of 'scissors' - a custom dataset. The output seems to be all over the place. While some are great to detect the pose, some are not. Do you have any thoughts?

Hello,

I have successfully completed training of the model; thank you for your support in that. I am running the code on an AWS instance; I am unable to view the visualization. Where would be the proper file to insert code to save the plots into a directory?

Would it be here?

The same thing for evaluate, where would be the file where I can alter it to save the evaluations to a file, because I am unable to view anything in a remote cluster.

For the command "conda create -n pvnet python=3.7", is pvnet a package that we need to download first ?
Thank you

你好，这个是怎么回事。在网上搜了搜，还是没有解决。麻烦您看看，谢谢。

May I pause training and continue training next time,due to the limitation I could use for training.
Thank you !

I got the image from your pretrained model. Do you have any ideas with this problem? thank you and your project

我用pvnet在我自己的小数据集上进行训练，然后进行预测。在ransac_voting阶段，经常碰到RuntimeError: solve_cuda: For batch 0: U(1,1) is zero, singular U 这个错误
错误发生在这里
def b_inv(b_mat): ''' code from https://stackoverflow.com/questions/46595157/how-to-apply-the-torch-inverse-function-of-pytorch-to-every-sample-in-the-batc :param b_mat: :return: ''' eye = b_mat.new_ones(b_mat.size(-1)).diag().expand_as(b_mat) b_inv, _ = torch.solve(eye, b_mat) return b_inv
请问有什么解决办法吗

torch 1.3.1
torchvision 0.4.2
windows10系统

From the example custom dataset, I see that for each image you need to have a 3x4 matrix with the pose saved in a numpy array. E.g. one of these arrays has the pose

[ -0.857243  ,  0.376382  , -0.351385  , -0.06970996],
[  0.499056  ,  0.775362  , -0.386984  , -0.0512582 ],
[  0.126797  , -0.5071      , -0.852509  ,  0.746117  ]

What is the format of this pose matrix (i.e. what does each of the entries mean)?

I have a custom dataset for which I would like to run through Clean-pvnet. I am following the instructions to run the run.py command for the custom dataset. I get the error below. I looked through the code for run.py and run_custom() function does not exist. Any information is greatly appreciated.

Traceback (most recent call last):
File "run.py", line 219, in
globals()'run_'+args.type
KeyError: 'run_custom'

I made Azure-kinect demo file. This file worked normally on my computer(Ubuntu 18.04, RTX 2080 Ti, CUDA 10.1)

https://hyu-my.sharepoint.com/:u:/g/personal/wdrac331_hanyang_ac_kr/EY7ODSE0DL5EoEK150cIW-IBAN71KNMlcMqjK1MP2kFdTw?e=82MTHR

However, an error occurs 20 to 30 seconds after operation.
The following is the error information.

[xcb] Unknown request in queue while dequeuing
[xcb] Most likely this is a multi-threaded client and XInitThreads has not been called
[xcb] Aborting, sorry about that.
python3: ../../src/xcb_io.c:165: dequeue_pending_request: Assertion
`!xcb_xlib_unknown_req_in_deq' failed.
: Fatal IO error: client killed

Have you ever seen such an error?

感谢作者的分享！
请问作者如何用训练出来的weight 来实时(Realtime)检测object的pose呢？
例如像主页里发布的Real-time-demo视频一样，可以在编码上稍微指点一下实时检测物体位姿的部分吗？
期待作者的回复，谢谢！

感谢作者提供的干净版本的pvnet! 当我运行了python run.py --type visualize --cfg_file configs/linemod.yaml train.datset CustomTrain test.dataset CustomTrain model mycat这个以后，出现了这种error, AssertionError: Non-existent Key: train.dataset，该如何解决呢？

Is it possible to detect multiple instances in the same image?

Thank you

I saw your command which is like this
python run.py --type evaluate --cfg_file configs/linemod.yaml train.dataset CustomTrain test.dataset CustomTrain model mycat
On your custom object, you alaways use the CustomTrain on the train.dataset and test.dataset.Does it mean that you use the same data on traning and testing? Thanks you.

What is the format of camera.txt in custom dataset ?
Organize the dataset as the following structure:
├── /path/to/dataset
│ ├── model.ply
│ ├── camera.txt
│ ├── rgb/
│ │ ├── 0.jpg
│ │ ├── ...
│ │ ├── 1234.jpg
│ │ ├── ...
│ ├── mask/
│ │ ├── 0.png
│ │ ├── ...
│ │ ├── 1234.png
│ │ ├── ...
│ ├── pose/
│ │ ├── 0.npy
│ │ ├── ...
│ │ ├── 1234.npy
│ │ ├── ...
│ │ └──

And I'd like to see an eample of this camera.txt. there's no such file camera.txt In LINEMOD dataset

Hi, thanks for your work. When I ran "python train_net.py --cfg_file configs/linemod.yaml model mycat cls_type cat", I met the followig error:

Traceback (most recent call last):
File "train_net.py", line 1, in
from lib.config import cfg, args
File "/home/yang/clean-pvnet-master/lib/config/init.py", line 1, in
from .config import cfg, args
File "/home/yang/clean-pvnet-master/lib/config/config.py", line 147, in
cfg = make_cfg(args)
File "/home/yang/clean-pvnet-master/lib/config/config.py", line 130, in make_cfg
cfg.merge_from_file(args.cfg_file)
File "/home/yang/anaconda3/envs/pvnet/lib/python3.6/site-packages/yacs/config.py", line 171, in merge_from_file
self.merge_from_other_cfg(cfg)
File "/home/yang/anaconda3/envs/pvnet/lib/python3.6/site-packages/yacs/config.py", line 175, in merge_from_other_cfg
_merge_a_into_b(cfg_other, self, self, [])
File "/home/yang/anaconda3/envs/pvnet/lib/python3.6/site-packages/yacs/config.py", line 401, in _merge_a_into_b
_merge_a_into_b(v, b[k], root, key_list + [k])
File "/home/yang/anaconda3/envs/pvnet/lib/python3.6/site-packages/yacs/config.py", line 392, in _merge_a_into_b
raise KeyError("Non-existent config key: {}".format(full_key))
KeyError: 'Non-existent config key: train.sampler'

I don't know how to solve it. And I am looking forward your reply. Thanks!

Could you please add the visualization about TLESS.
Very Thanks!

When i try to visualize, after this

loading annotations into memory...
Done (t=0.03s)
creating index...
index created!
loading annotations into memory...
Done (t=0.05s)
creating index...
index created!

comes error:

sac_voting/ransac_voting_gpu.py", line 135, in ransac_voting_layer_v3
    cur_mask *= selected_mask
RuntimeError: expected device cuda:0 and dtype Byte but got device cuda:0 and dtype Bool

I am running the code on a Mac os, can I still run inference using the CAT pertained model?

I copied all the compiled file directories (which successfully runs inference on the aws gpu instance) onto to my local machine. But when, I run the visualize command on my cpu, I am getting the error below. Do I need a GPU to run inference ? My goal is to build a real time functioning pose estimator using a real sense camera to visualize the pose in real time. It would be difficult to build this from a remote aws instance.

File "run.py", line 91, in run_visualize
network = make_network(cfg)#.cuda()
File "/Users/ishangupta/Documents/Python_Projects/pose-demo/aws-clean-pvnet/clean-pvnet/lib/networks/make_network.py", line 34, in make_network
return imp.load_source(module, path).get_network(cfg)
File "/Users/ishangupta/.pyenv/versions/3.7.0/lib/python3.7/imp.py", line 172, in load_source
module = _load(spec)
File "", line 696, in _load
File "", line 677, in _load_unlocked
File "", line 728, in exec_module
File "", line 219, in _call_with_frames_removed
File "lib/networks/pvnet/init.py", line 1, in
from .resnet18 import get_res_pvnet
File "lib/networks/pvnet/resnet18.py", line 5, in
from lib.csrc.ransac_voting.ransac_voting_gpu import ransac_voting_layer, ransac_voting_layer_v3
File "/Users/ishangupta/Documents/Python_Projects/pose-demo/aws-clean-pvnet/clean-pvnet/lib/csrc/ransac_voting/ransac_voting_gpu.py", line 2, in
import lib.csrc.ransac_voting.ransac_voting as ransac_voting
ModuleNotFoundError: No module named 'lib.csrc.ransac_voting.ransac_voting'

Hello,

I have created a custom dataset (the dataset is in the exact format as the linemod dataset). These are some errors I am facing when running:

python run.py --type custom

Error 1
Traceback (most recent call last):
File "run.py", line 226, in
globals()'run_'+args.type
File "run.py", line 222, in run_custom
handle_custom_dataset.custom_to_coco(data_root)
File "/home/ubuntu/clean-pvnet/tools/handle_custom_dataset.py", line 89, in custom_to_coco
renderer = OpenGLRenderer(model_path)
File "/home/ubuntu/clean-pvnet/lib/utils/linemod/opengl_renderer.py", line 21, in init
self.model = self.load_ply(self.ply_path)
File "/home/ubuntu/clean-pvnet/lib/utils/linemod/opengl_renderer.py", line 42, in load_ply
line = f.readline().rstrip('\n').rstrip('\r') # Strip the newline character(s)
File "/home/ubuntu/anaconda3/envs/pvnet/lib/python3.7/codecs.py", line 322, in decode

UnicodeDecodeError: 'utf-8' codec can't decode byte 0xf3 in position 292: invalid continuation byte

I was able to bypass this error by running the code on a Python 2 environment and saving the dictionary into a .npz file then manually loading the dictionary in the python 3 environment. But essentially the function in opengl_renderer.py ---- def load_ply(self, ply_path): only works in a python 2 environment.

Error 2 (Currently stuck on)
When running the train command:

python train_net.py --cfg_file configs/linemod.yaml train.dataset CustomTrain test.dataset CustomTrain model mycat train.batch_size 4

I get this error: FileNotFoundError: [Errno 2] No such file or directory: 'data/linemod/cat/cat.ply'

But I am not trying to use a cat, I have my own .ply file called model.ply which is stored in the directory structure mentioned in the repo like below:

├── /path/to/dataset
│ ├── model.ply
│ ├── camera.txt
│ ├── rgb/
│ │ ├── 0.jpg
│ │ ├── ...
│ │ ├── 1234.jpg
│ │ ├── ...
│ ├── mask/
│ │ ├── 0.png
│ │ ├── ...
│ │ ├── 1234.png
│ │ ├── ...
│ ├── pose/
│ │ ├── 0.npy
│ │ ├── ...
│ │ ├── 1234.npy
│ │ ├── ...
│ │ └──

Any information is greatly appreciated.

Hello! I downloaded the repo, datasets and followed the installation guide here on the repo but do not manage to run the python train_net.py --cfg_file configs/tless/tless_01.yaml command. I attach the terminal output. Just like the error says there are missing files.

When pressing the 5:th link under the list of datasets it takes me to a list of 14 items and I chose the first i.e. "tlessaa". Do I need them all? Because the one I chose does not contain train_primesense which the code tries to execute.

Thanks in advance!

python train_net.py --cfg_file configs/tless/tless_01.yaml
loading annotations into memory...
Done (t=3.07s)
creating index...
index created!
lib/evaluators/tless_test/pvnet.py:42: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
model_info = yaml.load(open(os.path.join(model_dir, 'models_info.yml')))
/home/franswed/anaconda3/envs/pvnet/lib/python3.7/site-packages/imgaug/imgaug.py:184: DeprecationWarning: Function ContrastNormalization() is deprecated. Use imgaug.contrast.LinearContrast instead.
warn_deprecated(msg, stacklevel=3)
loading annotations into memory...
Done (t=0.02s)
creating index...
index created!
loading annotations into memory...
Traceback (most recent call last):
File "train_net.py", line 57, in
main()
File "train_net.py", line 53, in main
train(cfg, network)
File "train_net.py", line 22, in train
train_loader = make_data_loader(cfg, is_train=True, max_iter=cfg.ep_iter)
File "/home/franswed/Documents/MastersThesis2020/clean-pvnet-master/lib/datasets/make_dataset.py", line 73, in make_data_loader
dataset = make_dataset(cfg, dataset_name, transforms, is_train)
File "/home/franswed/Documents/MastersThesis2020/clean-pvnet-master/lib/datasets/make_dataset.py", line 32, in make_dataset
dataset = dataset(**args)
File "lib/datasets/tless_train/pvnet.py", line 46, in init
self.other_obj_coco = COCO('data/tless/train_primesense/assets/train.json')
File "/home/franswed/anaconda3/envs/pvnet/lib/python3.7/site-packages/pycocotools/coco.py", line 84, in init
dataset = json.load(open(annotation_file, 'r'))
FileNotFoundError: [Errno 2] No such file or directory: 'data/tless/train_primesense/assets/train.json'

Hello.

I changed GPU to RTX2080 series this time.
Therefore, cuda 10.0 was installed. RTX does not support cuda 9.0.
But there is a problem setting the ransac voting.

Is there any place to modify cuda path other than the following?
https://github.com/zju3dv/clean-pvnet/blob/master/lib/csrc/nn/setup.py#L3

Always be careful of infection and hope nothing happens.

Regards,
David

Hi,

I tried to train your network on the Ape object. So I ran the command :
python train_net.py --cfg_file configs/linemod.yaml model ape cls_type ape but after 200 epochs I cannot find the same results than you. I followed every steps of your tutorial.

Regards

Hi,thanks your perfect work.
I want to know "when you use TLESS dataset, how did you settle the original dataset?" Can I use the same way like the custom dataset to handle the TLESS dataset?
Thanks!