graspnetAPI
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Toolbox for our GraspNet-1Billion dataset.
您好,最近在github上看你们的代码,这里我把你们数据集的前110个scene使用convert脚本转换成.npy文件,使用exam_eval.py脚本进行评估,遇到了以下错误: Traceback (most recent call last): File "/home/robot/graspnetAPI-master/examples/exam_eval.py", line 21, in acc = ge_r.eval_scene(scene_id=sceneId, dump_folder=dump_folder) File "/home/robot/graspnetAPI-master/graspnetAPI/graspnet_eval.py", line 144, in eval_scene grasp_list, score_list, collision_mask_list = eval_grasp(grasp_group, model_sampled_list, dexmodel_list, pose_list, config,...
Hi everyone. I am running the test.py file on a laptop with Ubuntu16 and 8 GB of RAM, under python 3.6, with a number of workers equal to 1. During...
How to get all grasps of pose for each object?
ERROR: Exception: Traceback (most recent call last): File "/home/lwh/anaconda3/envs/graspnet/lib/python3.12/site-packages/pip/_internal/cli/base_command.py", line 180, in exc_logging_wrapper status = run_func(*args) ^^^^^^^^^^^^^^^ File "/home/lwh/anaconda3/envs/graspnet/lib/python3.12/site-packages/pip/_internal/cli/req_command.py", line 245, in wrapper return func(self, options, args) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/lwh/anaconda3/envs/graspnet/lib/python3.12/site-packages/pip/_internal/commands/install.py",...
Install graspnetAPI Error Enviroment: Ubuntu 20.04 Anaconda Command: `pip install .` Solution: `export SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True` Error: ```bash Using cached sklearn-0.0.post9.tar.gz (3.6 kB) Preparing metadata (setup.py) ... error error: subprocess-exited-with-error × python...
× python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> [18 lines of output] The 'sklearn' PyPI package is deprecated, use 'scikit-learn' rather than 'sklearn' for pip...
Hello, I recently took a closer look at the objects used in your dataset. I found that the scenes 188 and 189 are completely comprised of objects which were already...
生成场景碰撞标签
首先感谢你们的杰出工作! 我尝试用数据集里的grasp_label及场景0000来生成场景的collision_label。原本我的想法是直接将整个场景所有物体的点级抓取构建为一个graspGroup,然后调用ModelFreeCollisionDetector函数得到colllision_mask,即为collision_labels。但是当我只将一个物体(id为0)的所有抓取构建为graspGroup,然后调用ModelFreeCollisionDetector函数时,遇到了内存不够的情况: `collision_detector.py", line 75, in detect targets = self.scene_points[np.newaxis,:,:] - T[:,np.newaxis,:] numpy.core._exceptions.MemoryError: Unable to allocate 19.5 TiB for an array with shape (49809600, 17901, 3) and data type float64`...
Object id 75-87: DexNet adversarial objects, 3D printed. Download mesh from [here](https://berkeley.app.box.com/s/w6bmvvkp399xtjpgskwq1cytkndmm7cn/folder/28003844491)这个链接失效
Signed-off-by: Max Waterhout