Comments (36)
akshay-bapat-magna
commented on August 22, 2024
This is possibly a typo. The ref/ directory contains lmo_full.py so it is likely referring to that module.
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yinguoxiangyi
commented on August 22, 2024
But there are many ref.lm_full in the file lm_syn_imgn.py, are you sure it's a typo?
I will replace all the lm_full with lmo_full and have a try.
Another question is where is the config file in the following commands? Could you please provide some sample commands?
./det/yolox/tools/test_yolox.sh <config_path> <gpu_ids> <ckpt_path> (other args)
./core/gdrn_modeling/test_gdrn.sh <config_path> <gpu_ids> <ckpt_path> (other args)
./core/gdrn_modeling/test_gdrn_depth_refine.sh <config_path> <gpu_ids> <ckpt_path> (other args)
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akshay-bapat-magna
commented on August 22, 2024
I am also trying to figure out the config file argument myself. I am also trying to use this repository for the first time, so even the lmo_full thing I mentioned is just my guess.
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yinguoxiangyi
commented on August 22, 2024
Uh strange, are you not the author of the repo?
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akshay-bapat-magna
commented on August 22, 2024
Nope! :)
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funnymind
commented on August 22, 2024
But there are many
ref.lm_fullin the filelm_syn_imgn.py, are you sure it's a typo? I will replace all thelm_fullwithlmo_fulland have a try.Another question is where is the config file in the following commands? Could you please provide some sample commands?
./det/yolox/tools/test_yolox.sh <config_path> <gpu_ids> <ckpt_path> (other args) ./core/gdrn_modeling/test_gdrn.sh <config_path> <gpu_ids> <ckpt_path> (other args) ./core/gdrn_modeling/test_gdrn_depth_refine.sh <config_path> <gpu_ids> <ckpt_path> (other args)
Hi
I am also looking into this solution.
For lm_full i try to use from this repo:
https://github.com/THU-DA-6D-Pose-Group/GDR-Net/tree/main/ref
For parameters i use like this:
./core/gdrn_modeling/test_gdrn.sh ./configs/gdrn/tless/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_tless.py 0 ./output/tless/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_tless/model_final_wo_optim.pth
Still under study, not sure how accurate this is.
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yinguoxiangyi
commented on August 22, 2024
@funnymind thanks for your hint, the location of lm_full you provide is probably true, I'll have a try.
And do you get the final test result successfully with your config? Is the evaluation result the same as the paper says?
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yinguoxiangyi
commented on August 22, 2024
Also, I think we need more help from the author @wangg12
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wangg12
commented on August 22, 2024
Hi, I guess it should be ok by changing lm_full to lmo_full since lm and lmo share the same id:name mapping. The issue might be caused by removing ref/lm_full.py but forgetting to change some necessary codes. @shanice-l
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yinguoxiangyi
commented on August 22, 2024
lm_full exist in many files, not only lm_syn_imgn.py. The modification of code may be so much
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funnymind
commented on August 22, 2024
if there is no difference in the content, then it may be easier to just copy lmo_full file to lm_full ?
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shanice-l
commented on August 22, 2024
Sry for the missing files.
I've uploaded it in the nearest commit.
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shanice-l
commented on August 22, 2024
But there are many
ref.lm_fullin the filelm_syn_imgn.py, are you sure it's a typo? I will replace all thelm_fullwithlmo_fulland have a try.Another question is where is the config file in the following commands? Could you please provide some sample commands?
./det/yolox/tools/test_yolox.sh <config_path> <gpu_ids> <ckpt_path> (other args) ./core/gdrn_modeling/test_gdrn.sh <config_path> <gpu_ids> <ckpt_path> (other args) ./core/gdrn_modeling/test_gdrn_depth_refine.sh <config_path> <gpu_ids> <ckpt_path> (other args)
I've also updated the readme. Now you can find some examples of using these commands.
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yinguoxiangyi
commented on August 22, 2024
Thanks very much, but another error occurred as following.
root@96d962c42873:/workspace/gdrnpp_bop2022# ./det/yolox/tools/test_yolox.sh configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py 0 output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
++ dirname ./det/yolox/tools/test_yolox.sh
+ this_dir=./det/yolox/tools
+ CFG=configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py
+ CUDA_VISIBLE_DEVICES=0
+ IFS=,
+ read -ra GPUS
+ NGPU=1
+ echo 'use gpu ids: 0 num gpus: 1'
use gpu ids: 0 num gpus: 1
+ CKPT=output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
+ '[' '!' -f output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth ']'
+ NCCL_DEBUG=INFO
+ OMP_NUM_THREADS=1
+ MKL_NUM_THREADS=1
+ PYTHONPATH=./det/yolox/tools/../..:
+ CUDA_VISIBLE_DEVICES=0
+ python ./det/yolox/tools/main_yolox.py --config-file configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py --num-gpus 1 --eval-only train.init_checkpoint=output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
You requested to import horovod which is missing or not supported for your OS.
Traceback (most recent call last):
File "./det/yolox/tools/main_yolox.py", line 31, in <module>
from det.yolox.data.datasets.dataset_factory import register_datasets_in_cfg
File "/workspace/gdrnpp_bop2022/det/yolox/tools/../../../det/yolox/data/datasets/dataset_factory.py", line 5, in <module>
from . import (
File "/workspace/gdrnpp_bop2022/det/yolox/tools/../../../det/yolox/data/datasets/lm_dataset_d2.py", line 694, in <module>
with open(cur_ann_file, "r") as f:
FileNotFoundError: [Errno 2] No such file or directory: '/workspace/gdrnpp_bop2022/datasets/BOP_DATASETS/lm/image_set/ape_train.txt'
Does image_set/ape_train.txt exist in LM train dataset. I use the following command to download the dataset, but can't find the file.
export SRC=https://bop.felk.cvut.cz/media/data/bop_datasets
wget $SRC/lm_base.zip # Base archive with dataset info, camera parameters, etc.
wget $SRC/lm_models.zip # 3D object models.
wget $SRC/lm_test_all.zip # All test images ("_bop19" for a subset used in the BOP Challenge 2019/2020).
wget $SRC/lm_train_pbr.zip # PBR training images (rendered with BlenderProc4BOP).
unzip lm_base.zip # Contains folder "lm".
unzip lm_models.zip -d lm # Unpacks to "lm".
unzip lm_test_all.zip -d lm # Unpacks to "lm".
unzip lm_train_pbr.zip -d lm # Unpacks to "lm".
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shanice-l
commented on August 22, 2024
Actually, the files for LM dataset are useless. I've removed them in the nearest commit.
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yinguoxiangyi
commented on August 22, 2024
Also, another error occurred. It is likely that hb_bdp is also missing in ref directory.
root@96d962c42873:/workspace/gdrnpp_bop2022# ./det/yolox/tools/test_yolox.sh configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py 0 output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
++ dirname ./det/yolox/tools/test_yolox.sh
+ this_dir=./det/yolox/tools
+ CFG=configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py
+ CUDA_VISIBLE_DEVICES=0
+ IFS=,
+ read -ra GPUS
+ NGPU=1
+ echo 'use gpu ids: 0 num gpus: 1'
use gpu ids: 0 num gpus: 1
+ CKPT=output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
+ '[' '!' -f output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth ']'
+ NCCL_DEBUG=INFO
+ OMP_NUM_THREADS=1
+ MKL_NUM_THREADS=1
+ PYTHONPATH=./det/yolox/tools/../..:
+ CUDA_VISIBLE_DEVICES=0
+ python ./det/yolox/tools/main_yolox.py --config-file configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py --num-gpus 1 --eval-only train.init_checkpoint=output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
You requested to import horovod which is missing or not supported for your OS.
Traceback (most recent call last):
File "./det/yolox/tools/main_yolox.py", line 31, in <module>
from det.yolox.data.datasets.dataset_factory import register_datasets_in_cfg
File "/workspace/gdrnpp_bop2022/det/yolox/tools/../../../det/yolox/data/datasets/dataset_factory.py", line 5, in <module>
from . import (
File "/workspace/gdrnpp_bop2022/det/yolox/tools/../../../det/yolox/data/datasets/hb_bench_driller_phone_d2.py", line 475, in <module>
for obj in ref.hb_bdp.objects:
AttributeError: module 'ref' has no attribute 'hb_bdp'
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shanice-l
commented on August 22, 2024
I've deleted hb_bench_driller_phone_d2.py also in the latest commit.
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yinguoxiangyi
commented on August 22, 2024
The file lm_dataset_d2.py is added again, should it have been removed?
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shanice-l
commented on August 22, 2024
lm_dataset_d2.py is necessary since it's provide test set for lmo.
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yinguoxiangyi
commented on August 22, 2024
But this file caused following error.
root@96d962c42873:/workspace/gdrnpp_bop2022# ./det/yolox/tools/test_yolox.sh configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py 0 output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
++ dirname ./det/yolox/tools/test_yolox.sh
+ this_dir=./det/yolox/tools
+ CFG=configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py
+ CUDA_VISIBLE_DEVICES=0
+ IFS=,
+ read -ra GPUS
+ NGPU=1
+ echo 'use gpu ids: 0 num gpus: 1'
use gpu ids: 0 num gpus: 1
+ CKPT=output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
+ '[' '!' -f output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth ']'
+ NCCL_DEBUG=INFO
+ OMP_NUM_THREADS=1
+ MKL_NUM_THREADS=1
+ PYTHONPATH=./det/yolox/tools/../..:
+ CUDA_VISIBLE_DEVICES=0
+ python ./det/yolox/tools/main_yolox.py --config-file configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py --num-gpus 1 --eval-only train.init_checkpoint=output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth
You requested to import horovod which is missing or not supported for your OS.
Traceback (most recent call last):
File "./det/yolox/tools/main_yolox.py", line 31, in <module>
from det.yolox.data.datasets.dataset_factory import register_datasets_in_cfg
File "/workspace/gdrnpp_bop2022/det/yolox/tools/../../../det/yolox/data/datasets/dataset_factory.py", line 5, in <module>
from . import (
File "/workspace/gdrnpp_bop2022/det/yolox/tools/../../../det/yolox/data/datasets/lm_dataset_d2.py", line 694, in <module>
with open(cur_ann_file, "r") as f:
FileNotFoundError: [Errno 2] No such file or directory: '/workspace/gdrnpp_bop2022/datasets/BOP_DATASETS/lm/image_set/ape_train.txt'
from gdrnpp_bop2022.
shanice-l
commented on August 22, 2024
Oops. I'll rewrite and test the code immediately. Plz wait for a minute.
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yinguoxiangyi
commented on August 22, 2024
Thanks.
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shanice-l
commented on August 22, 2024
I think there is no further reliance on LM. Sry for the trouble.
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yinguoxiangyi
commented on August 22, 2024
The output of the command ./det/yolox/tools/test_yolox.sh configs/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test.py 0 output/yolox/bop_pbr/yolox_x_640_augCozyAAEhsv_ranger_30_epochs_lmo_pbr_lmo_bop_test/model_final.pth is below.
From your side, does the data meet the expectation?
[1102_065133 det.yolox.evaluators.yolox_coco_evaluator@383]: Evaluating predictions with unofficial COCO API...
Loading and preparing results...
DONE (t=0.23s)
creating index...
index created!
[1102_065133 d2.evaluation.fast_eval_api@33]: Evaluate annotation type *bbox*
[1102_065133 d2.evaluation.fast_eval_api@95]: COCOeval_opt.evaluate() finished in 0.24 seconds.
[1102_065133 d2.evaluation.fast_eval_api@103]: Accumulating evaluation results...
[1102_065133 d2.evaluation.fast_eval_api@121]: COCOeval_opt.accumulate() finished in 0.06 seconds.
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.635
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.905
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.731
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.279
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.697
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.733
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.676
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.688
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.696
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.295
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.754
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.774
[1102_065133 det.yolox.evaluators.yolox_coco_evaluator@471]: Evaluation results for bbox:
| AP | AP50 | AP75 | APs | APm | APl |
|:------:|:------:|:------:|:------:|:------:|:------:|
| 63.536 | 90.482 | 73.092 | 27.865 | 69.710 | 73.336 |
[1102_065133 det.yolox.evaluators.yolox_coco_evaluator@503]: Per-category bbox AP:
| category | AP | category | AP | category | AP |
|:-----------|:-------|:------------|:-------|:-----------|:-------|
| ape | 57.452 | can | 80.020 | cat | 54.236 |
| driller | 76.059 | duck | 69.249 | eggbox | 39.370 |
| glue | 55.871 | holepuncher | 76.031 | | |
[1102_065133 det.yolox.evaluators.yolox_coco_evaluator@533]: Per-category bbox AR:
| category | AR | category | AR | category | AR | category | AR | category | AR |
|:-----------|:-------|:-----------|:-------|:------------|:-------|:-----------|:-------|:-----------|:-------|
| ape | 64.225 | can | 83.467 | cat | 59.898 | driller | 80.200 | duck | 73.085 |
| eggbox | 55.233 | glue | 61.039 | holepuncher | 79.450 | | | | |
[1102_065133 det.yolox.engine.yolox_trainer@639]: Evaluation results for lmo_bop_test in csv format:
[1102_065133 d2.evaluation.testing@24]: copypaste: Task: bbox
[1102_065133 d2.evaluation.testing@25]: copypaste: AP,AP50,AP75,APs,APm,APl
[1102_065133 d2.evaluation.testing@26]: copypaste: 63.5360,90.4822,73.0919,27.8649,69.7097,73.3361
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shanice-l
commented on August 22, 2024
The evaluation results of Det are inaccurate. You can upload the csv files to the BOP system to get the accurate score.
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yinguoxiangyi
commented on August 22, 2024
Another error occurred when I ran the command ./core/gdrn_modeling/test_gdrn.sh configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py 0 output/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo/model_final_wo_optim.pth
Traceback (most recent call last):
> File "./core/gdrn_modeling/main_gdrn.py", line 233, in <module>
main(args)
│ └ Namespace(config_file='configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py', dist...
└ <function main at 0x7fa2275fe710>
File "./core/gdrn_modeling/main_gdrn.py", line 205, in main
).run(args, cfg)
│ └ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT...
└ Namespace(config_file='configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py', dist...
File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/lite/lite.py", line 402, in _run_impl
return run_method(*args, **kwargs)
│ │ └ {}
│ └ (Namespace(config_file='configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py', dis...
└ functools.partial(<bound method LightningLite._run_with_strategy_setup of <__main__.Lite object at 0x7fa22826e590>>, <bound m...
File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/lite/lite.py", line 409, in _run_with_strategy_setup
return run_method(*args, **kwargs)
│ │ └ {}
│ └ (Namespace(config_file='configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py', dis...
└ <bound method Lite.run of <__main__.Lite object at 0x7fa22826e590>>
File "./core/gdrn_modeling/main_gdrn.py", line 183, in run
return self.do_test(cfg, model)
│ │ │ └ _LiteModule(
│ │ │ (_forward_module): GDRN_DoubleMask(
│ │ │ (backbone): FeatureListNet(
│ │ │ (stem_0): Conv2d(3, 128, kernel_size...
│ │ └ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT...
│ └ <function GDRN_Lite.do_test at 0x7fa2279f4950>
└ <__main__.Lite object at 0x7fa22826e590>
File "/workspace/gdrnpp_bop2022/core/gdrn_modeling/../../core/gdrn_modeling/engine/engine.py", line 157, in do_test
data_loader = build_gdrn_test_loader(cfg, dataset_name, train_objs=evaluator.train_objs)
│ │ │ │ └ ['ape', 'can', 'cat', 'driller', 'duck', 'eggbox', 'glue', 'holepuncher']
│ │ │ └ <core.gdrn_modeling.engine.gdrn_evaluator.GDRN_Evaluator object at 0x7fa2d7229a50>
│ │ └ 'lmo_bop_test'
│ └ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT...
└ <function build_gdrn_test_loader at 0x7fa227a31050>
File "/workspace/gdrnpp_bop2022/core/gdrn_modeling/../../core/gdrn_modeling/datasets/data_loader.py", line 934, in build_gdrn_test_loader
selected_scenes=cfg.DATASETS.get("EVAL_SCENE_IDS", None),
└ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT...
File "/workspace/gdrnpp_bop2022/core/gdrn_modeling/../../core/utils/dataset_utils.py", line 167, in load_detections_into_dataset
detections = mmcv.load(det_file)
│ │ └ 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json'
│ └ <function load at 0x7fa301228200>
└ <module 'mmcv' from '/opt/conda/lib/python3.7/site-packages/mmcv/__init__.py'>
File "/opt/conda/lib/python3.7/site-packages/mmcv/fileio/io.py", line 64, in load
with StringIO(file_client.get_text(file)) as f:
│ │ │ └ 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json'
│ │ └ <function FileClient.get_text at 0x7fa2f995ac20>
│ └ <mmcv.fileio.file_client.FileClient object at 0x7fa227c95590>
└ <class '_io.StringIO'>
File "/opt/conda/lib/python3.7/site-packages/mmcv/fileio/file_client.py", line 1027, in get_text
return self.client.get_text(filepath, encoding)
│ │ │ │ └ 'utf-8'
│ │ │ └ 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json'
│ │ └ <function HardDiskBackend.get_text at 0x7fa2f997eef0>
│ └ <mmcv.fileio.file_client.HardDiskBackend object at 0x7fa2275e20d0>
└ <mmcv.fileio.file_client.FileClient object at 0x7fa227c95590>
File "/opt/conda/lib/python3.7/site-packages/mmcv/fileio/file_client.py", line 552, in get_text
with open(filepath, encoding=encoding) as f:
│ └ 'utf-8'
└ 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json'
FileNotFoundError: [Errno 2] No such file or directory: 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json'
root@4bc8d44c51fb:/workspace/gdrnpp_bop2022# ls datasets/BOP_DATASETS/lmo/test/test_bboxes/
yolox_x_640_lmo_pbr_lmo_bop_test.json
root@4bc8d44c51fb:/workspace/gdrnpp_bop2022#
Maybe the filename of test_bboxes has changed.
from gdrnpp_bop2022.
shanice-l
commented on August 22, 2024
Another error occurred when I ran the command
./core/gdrn_modeling/test_gdrn.sh configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py 0 output/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo/model_final_wo_optim.pthTraceback (most recent call last): > File "./core/gdrn_modeling/main_gdrn.py", line 233, in <module> main(args) │ └ Namespace(config_file='configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py', dist... └ <function main at 0x7fa2275fe710> File "./core/gdrn_modeling/main_gdrn.py", line 205, in main ).run(args, cfg) │ └ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT... └ Namespace(config_file='configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py', dist... File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/lite/lite.py", line 402, in _run_impl return run_method(*args, **kwargs) │ │ └ {} │ └ (Namespace(config_file='configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py', dis... └ functools.partial(<bound method LightningLite._run_with_strategy_setup of <__main__.Lite object at 0x7fa22826e590>>, <bound m... File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/lite/lite.py", line 409, in _run_with_strategy_setup return run_method(*args, **kwargs) │ │ └ {} │ └ (Namespace(config_file='configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py', dis... └ <bound method Lite.run of <__main__.Lite object at 0x7fa22826e590>> File "./core/gdrn_modeling/main_gdrn.py", line 183, in run return self.do_test(cfg, model) │ │ │ └ _LiteModule( │ │ │ (_forward_module): GDRN_DoubleMask( │ │ │ (backbone): FeatureListNet( │ │ │ (stem_0): Conv2d(3, 128, kernel_size... │ │ └ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT... │ └ <function GDRN_Lite.do_test at 0x7fa2279f4950> └ <__main__.Lite object at 0x7fa22826e590> File "/workspace/gdrnpp_bop2022/core/gdrn_modeling/../../core/gdrn_modeling/engine/engine.py", line 157, in do_test data_loader = build_gdrn_test_loader(cfg, dataset_name, train_objs=evaluator.train_objs) │ │ │ │ └ ['ape', 'can', 'cat', 'driller', 'duck', 'eggbox', 'glue', 'holepuncher'] │ │ │ └ <core.gdrn_modeling.engine.gdrn_evaluator.GDRN_Evaluator object at 0x7fa2d7229a50> │ │ └ 'lmo_bop_test' │ └ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT... └ <function build_gdrn_test_loader at 0x7fa227a31050> File "/workspace/gdrnpp_bop2022/core/gdrn_modeling/../../core/gdrn_modeling/datasets/data_loader.py", line 934, in build_gdrn_test_loader selected_scenes=cfg.DATASETS.get("EVAL_SCENE_IDS", None), └ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT... File "/workspace/gdrnpp_bop2022/core/gdrn_modeling/../../core/utils/dataset_utils.py", line 167, in load_detections_into_dataset detections = mmcv.load(det_file) │ │ └ 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json' │ └ <function load at 0x7fa301228200> └ <module 'mmcv' from '/opt/conda/lib/python3.7/site-packages/mmcv/__init__.py'> File "/opt/conda/lib/python3.7/site-packages/mmcv/fileio/io.py", line 64, in load with StringIO(file_client.get_text(file)) as f: │ │ │ └ 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json' │ │ └ <function FileClient.get_text at 0x7fa2f995ac20> │ └ <mmcv.fileio.file_client.FileClient object at 0x7fa227c95590> └ <class '_io.StringIO'> File "/opt/conda/lib/python3.7/site-packages/mmcv/fileio/file_client.py", line 1027, in get_text return self.client.get_text(filepath, encoding) │ │ │ │ └ 'utf-8' │ │ │ └ 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json' │ │ └ <function HardDiskBackend.get_text at 0x7fa2f997eef0> │ └ <mmcv.fileio.file_client.HardDiskBackend object at 0x7fa2275e20d0> └ <mmcv.fileio.file_client.FileClient object at 0x7fa227c95590> File "/opt/conda/lib/python3.7/site-packages/mmcv/fileio/file_client.py", line 552, in get_text with open(filepath, encoding=encoding) as f: │ └ 'utf-8' └ 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json' FileNotFoundError: [Errno 2] No such file or directory: 'datasets/BOP_DATASETS/lmo/test/test_bboxes/yolov4x_amodal_lmo_pbr_bop.json' root@4bc8d44c51fb:/workspace/gdrnpp_bop2022# ls datasets/BOP_DATASETS/lmo/test/test_bboxes/ yolox_x_640_lmo_pbr_lmo_bop_test.json root@4bc8d44c51fb:/workspace/gdrnpp_bop2022#Maybe the filename of test_bboxes has changed.
Thanks for figuring out that!! The bug has been fixed.
from gdrnpp_bop2022.
wangg12
commented on August 22, 2024
The evaluation results of Det are inaccurate. You can upload the csv files to the BOP system to get the accurate score.
After update, This line
is not using amodal box.from gdrnpp_bop2022.
yinguoxiangyi
commented on August 22, 2024
The evaluation results of Det are inaccurate. You can upload the csv files to the BOP system to get the accurate score.
After update, This line
is not using amodal box.
I am not very clear about why you say the Det test result is inaccurate. Is the inaccuracy caused by no using of amodal box?
from gdrnpp_bop2022.
yinguoxiangyi
commented on August 22, 2024
How about below pose estimation result? Is this accurate? The following result is the output of ./core/gdrn_modeling/test_gdrn.sh configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py 0 output/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo/model_final_wo_optim.pth
20221103_033737|core.gdrn_modeling.engine.test_utils@453:
objects mspd_5:50 mssd_0.050:0.500 vsd_0.050:0.500 ad_0.020 ad_0.050 ad_0.100 reS_2 reS_5 reS_10 teS_2 teS_5 teS_10
ape 91.71 71.94 51.53 1.14 13.14 48.00 12.57 63.43 88.00 81.14 95.43 96.57
can 93.77 83.77 69.20 2.51 38.19 83.42 40.70 79.90 95.98 82.91 95.48 99.50
cat 91.75 66.55 51.52 1.75 16.96 48.54 14.62 45.03 78.36 59.65 86.55 93.57
driller 91.25 87.75 73.51 6.50 53.00 86.00 50.50 83.50 97.50 77.50 96.50 99.00
duck 90.89 53.22 49.27 0.00 1.67 8.89 9.44 29.44 71.67 52.78 95.56 98.89
eggbox 63.56 30.06 18.03 1.11 8.33 34.44 0.56 18.89 65.00 10.00 43.33 69.44
glue 85.93 68.50 49.74 10.71 54.29 76.43 10.00 35.71 74.29 55.71 85.00 95.00
holepuncher 89.75 66.15 47.08 0.50 5.50 27.00 26.50 64.50 94.00 43.00 95.50 98.00
Avg(8) 87.49 66.44 51.76 3.03 23.88 51.59 20.61 52.55 83.10 57.84 86.67 93.75
20221103_033737|core.gdrn_modeling.engine.test_utils@453:
objects ape can cat driller duck eggbox glue holepuncher Avg(8)
mspd_5:50 91.71 93.77 91.75 91.25 90.89 63.56 85.93 89.75 87.49
mssd_0.050:0.500 71.94 83.77 66.55 87.75 53.22 30.06 68.50 66.15 66.44
vsd_0.050:0.500 51.53 69.20 51.52 73.51 49.27 18.03 49.74 47.08 51.76
ad_0.020 1.14 2.51 1.75 6.50 0.00 1.11 10.71 0.50 3.03
ad_0.050 13.14 38.19 16.96 53.00 1.67 8.33 54.29 5.50 23.88
ad_0.100 48.00 83.42 48.54 86.00 8.89 34.44 76.43 27.00 51.59
reS_2 12.57 40.70 14.62 50.50 9.44 0.56 10.00 26.50 20.61
reS_5 63.43 79.90 45.03 83.50 29.44 18.89 35.71 64.50 52.55
reS_10 88.00 95.98 78.36 97.50 71.67 65.00 74.29 94.00 83.10
teS_2 81.14 82.91 59.65 77.50 52.78 10.00 55.71 43.00 57.84
teS_5 95.43 95.48 86.55 96.50 95.56 43.33 85.00 95.50 86.67
teS_10 96.57 99.50 93.57 99.00 98.89 69.44 95.00 98.00 93.75
100%|##########| 1/1 [00:00<00:00, 19.24it/s]
20221103_033737|core.gdrn_modeling.engine.test_utils@456: output/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo/inference_model_final_wo_optim/lmo_bop_test
20221103_033737|core.gdrn_modeling.engine.test_utils@80: eval time: 483.81608146600774s
from gdrnpp_bop2022.
yinguoxiangyi
commented on August 22, 2024
When to do pose refinement, is the args of test_gdrn_depth_refine.sh the same as test_gdrn.sh?
from gdrnpp_bop2022.
yinguoxiangyi
commented on August 22, 2024
If I use this command ./core/gdrn_modeling/test_gdrn_depth_refine.sh configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py 0 output/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo/model_final_wo_optim.pth which args are same as test_gdrn.sh, error occurred as following.
File "/workspace/gdrnpp_bop2022/core/gdrn_modeling/../../core/gdrn_modeling/engine/gdrn_evaluator.py", line 81, in __init__
texture_paths=self.data_ref.texture_paths if cfg.TEST.DEBUG else None,
│ │ │ └ Config (path: configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py): {'OUTPUT_ROOT...
│ │ └ None
│ └ <module 'ref.lmo_full' from '/workspace/gdrnpp_bop2022/core/gdrn_modeling/../../ref/lmo_full.py'>
└ <core.gdrn_modeling.engine.gdrn_evaluator.GDRN_Evaluator object at 0x7fa7238bb410>
File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/config.py", line 50, in __getattr__
raise ex
└ AttributeError("'ConfigDict' object has no attribute 'DEBUG'")
AttributeError: 'ConfigDict' object has no attribute 'DEBUG'
Seems there is not TEST.DEBUG in configs/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo.py
from gdrnpp_bop2022.
shanice-l
commented on August 22, 2024
If you have new questions that are not related to this issue, plz start a new one.
from gdrnpp_bop2022.
shanice-l
commented on August 22, 2024
This issue has been solved. If you don't have any further problems, it will be closed in 3 days.
from gdrnpp_bop2022.
yinguoxiangyi
commented on August 22, 2024
Okay, thank you very much , I'll move the last 2 comments I submitted to a new issue. I think it is better to explain the inaccuracy problem in this issue because the context is related.
from gdrnpp_bop2022.
wangg12
commented on August 22, 2024
The evaluation results of Det are inaccurate. You can upload the csv files to the BOP system to get the accurate score.
After update, This line
is not using amodal box.
I am not very clear about why you say the Det test result is inaccurate. Is the inaccuracy caused by no using of amodal box?
This should be resolved in the latest commit.
from gdrnpp_bop2022.
Related Issues (20)
- script for visualizing the results on tless dataset HOT 1
- RuntimeError: output/gdrn/lmo_pbr/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_lmo/inference_model_final_wo_optim/lmo_bop_test/convnext-a6-AugCosyAAEGray-BG05-mlL1-DMask-amodalClipBox-classAware-lmo-test-iter0_lmo-test/error:vsd_ntop:1_delta:15.000_tau:0.050 does not exist. HOT 3
- visualizing results of inference on lmo -- FileNotFoundError: [Errno 2] No such file or directory: 'output/gdrn/lmo/a6_cPnP_AugAAETrunc_BG0.5_lmo_real_pbr0.1_40e/inference_model_final/lmo_test/a6-cPnP-AugAAETrunc-BG0.5-lmo-real-pbr0.1-40e-test_lmo_test_preds.pkl' HOT 1
- visualizing result of YCB-V inference FileNotFoundError: [Errno 2] No such file or directory: 'output/gdrn/ycbv/a6_cPnP_AugAAETrunc_BG0.5_ycbv_real_pbr_visib20_20e_allObjs/a6-cPnP-AugAAETrunc-BG0.5-ycbv-real-pbr-visib20-20e-singleObjMerged-bop-test-iter0_ycbv-test.csv' HOT 1
- ycbv results visualization only shows the contour around the objects not the projected 3D bounding box HOT 3
- problems in lmo visualization script HOT 4
- training procedure/code for a custom dataset made by BlenderProc that follows linemod format HOT 2
- Questions for training separate model for each object and depth refinement HOT 1
- [ERROR]: mask_trunc array size mismatch on custom dataset
- inference results are zero when using pretrained model weights for ycb-v HOT 1
- lmo_2_vis_poses.py", preds = mmcv.load(pred_path) TypeError: Unsupported format: csv HOT 1
- question regarding visib_gt_min HOT 1
- instruction for creation of files such as yolox_x_640_lmo_pbr_lmo_bop_test.json for a synthetic dataset made by BlenderProc HOT 1
- yolox_mona_test_bop.json missing for a synthetic dataset made with BOP
- Cholesky fails
- TypeError: FormatCode() got an unexpected keyword argument 'verify' HOT 1
- AttributeError: '_GeneratorContextManager' object has no attribute 'meshes' HOT 2
- Filtered out 271305 instances without valid box. There might be issues in your dataset generation process.
- KeyError: '135' when testing gdrnpp on ycbv HOT 1
- RuntimeError: output/gdrn/tless/convnext_a6_AugCosyAAEGray_BG05_mlL1_DMask_amodalClipBox_classAware_tless/inference_model_final_wo_optim/tless_bop_test_primesense/convnext-a6-AugCosyAAEGray-BG05-mlL1-DMask-amodalClipBox-classAware-tless-test-iter0_tless-test/error:vsd_ntop:-1_delta:15.000_tau:0.050 does not exist. HOT 1
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from gdrnpp_bop2022.