Tags: isl-org/Open3D-ML
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boundingbox.py: Changed np.int to np.int32 to make compatible with ne… …w versions of numpy (#624) numpy.int is deprecated (>=1.20) or removed (>=1.24). This is compatible back to >=1.13 and possibly earlier (earliest version for which online documentation exists) --------- Co-authored-by: Sameer Sheorey <sameer.sheorey@intel.com>
Dev (#197) * version update for next release * Add Kitti object detection dataset (#128) * Fix missing argument * more import bugfixes (#126) * fix missing attribute 'utils' * removed import statements for unused modules * fix conflict * add kitti dataset * address reviews Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> * Add Waymo Dataset (#136) * add waymo preprocess * add waymo class * added argparse * apply style * add docstring * remove cv2 * Add NuScenes dataset (#137) * add preprocess nuscenes * bug fix * add argparse * add nuscenes class * apply style * added label * Fix ignore class * add docstring * style * create sampler class for sampling point cloud idx and points idx (#135) * Fix missing argument * more import bugfixes (#126) * fix missing attribute 'utils' * removed import statements for unused modules * add readme about config files (#129) * readme about config files * link to predefined script * Update README.md * Simplified install instructions (#127) * Simpliefied install instructions Multiple requirements files for different use cases. * minor change to README * minor change adding link to docs for build from source. * update install instruction, add +cpu to torch requirements.txt Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> * added conditionals in requirements-torch for macos (#131) * Fix color dictionary in Semantic-KITTI bgr -> rgb (#130) * sampler * sampler class * Enable hierarchy UI feature in visualizer for SemanticKITTI (#133) * spatially regular * kpconv sampler * kpconv paris lille * delete debug information * valid * vlida * default sampler * confusion matrix Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> Co-authored-by: ssheorey <41028320+ssheorey@users.noreply.github.com> Co-authored-by: Ignacio Vizzo <ignaciovizzo@gmail.com> Co-authored-by: prewettg <prewettg@gmail.com> * Add Lyft Dataset (#138) * bug fix * Added preprocess lyft * bug * add dataset_class for lyft * style * bug fix Co-authored-by: germanros1987 <38517452+germanros1987@users.noreply.github.com> * apply-style * Download scripts (#145) * add kitti download script * fix semantickitti * added lyft download script * Add bounding boxes to visualizer (#140) * Add bounding boxes to visualizer * Dataset bounding boxes are now fully their own object and do hide auto-hide/show pieces associated with a geometry, but they do auto-hide irrelevant boxes when animating. * Style fixes * Added documentation, changed definition of size argument to be edge-to-edge and adjusted code accordingly * Create LICENSE * Change Bounding box class. (#149) * change bbox class * improve bbox * style * waymo bbox * added nuscenes bbox * added lyft bbox * apply style * fix waymo bbox * fix kitti bbox * apply style; * address review * Update README.md * Added Agroverse 3D Dataset (#155) * added argoverse * style * change classes * use open3d for reading pcd * link to kpconv parislille3d models in readme (#160) * readme for parislille3d kpconv models * PointPillars inference pipeline (#153) * Fix missing argument * more import bugfixes (#126) * fix missing attribute 'utils' * removed import statements for unused modules * fix conflict * add kitti dataset * add readme about config files (#129) * readme about config files * link to predefined script * Update README.md * address reviews * Simplified install instructions (#127) * Simpliefied install instructions Multiple requirements files for different use cases. * minor change to README * minor change adding link to docs for build from source. * update install instruction, add +cpu to torch requirements.txt Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> * added conditionals in requirements-torch for macos (#131) * Fix color dictionary in Semantic-KITTI bgr -> rgb (#130) * Enable hierarchy UI feature in visualizer for SemanticKITTI (#133) * PointPillars port from mmdet without NMS and Voxelizer. Only inference. Focal loss and smooth L1 implemented and tested. * loss function implemented and tested * Add bounding boxes to visualizer * Voxelization layer for point_pillars * apply style * Dataset bounding boxes are now fully their own object and do hide auto-hide/show pieces associated with a geometry, but they do auto-hide irrelevant boxes when animating. * Style fixes * objdet metric * removed mmdet3d dependency, o3d nms and voxelizer added * renamed objdet to run_pipeline, implemented part of the objdet pipeline * Added documentation, changed definition of size argument to be edge-to-edge and adjusted code accordingly * kitti eval only 3d boxes * test pipeline point pillars * howto small fix * change bbox class * improve bbox * style * visualization of results * test vis of results * using new bounding box class * waymo bbox * added nuscenes bbox * added lyft bbox * apply style * anchor head refactoring * fix waymo bbox * fix kitti bbox * apply style; * removed transformation of the predicted boxes * added licenses to files * removed unnecessary parts * format * Labels displayed in visualization. Kitti dataset label ordering changed to match MMDetection3D. * using our checkpoint format * fix ci * apply style * apply style * changed list to tuple Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> Co-authored-by: YilingQiao <49262224+YilingQiao@users.noreply.github.com> Co-authored-by: ssheorey <41028320+ssheorey@users.noreply.github.com> Co-authored-by: Ignacio Vizzo <ignaciovizzo@gmail.com> Co-authored-by: prewettg <prewettg@gmail.com> Co-authored-by: lprantl <lprantl@lprantl-DESK.imu.intel.com> * add comments for visualize predictions (#151) * Fix missing argument * more import bugfixes (#126) * fix missing attribute 'utils' * removed import statements for unused modules * add readme about config files (#129) * readme about config files * link to predefined script * Update README.md * Simplified install instructions (#127) * Simpliefied install instructions Multiple requirements files for different use cases. * minor change to README * minor change adding link to docs for build from source. * update install instruction, add +cpu to torch requirements.txt Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> * added conditionals in requirements-torch for macos (#131) * Fix color dictionary in Semantic-KITTI bgr -> rgb (#130) * Enable hierarchy UI feature in visualizer for SemanticKITTI (#133) * Import os (#148) I am getting also another error later about NameError Traceback (most recent call last) <ipython-input-5-bed5d0e06c9a> in <module> 22 pipeline_k.load_ckpt(model.cfg.ckpt_path) 23 ---> 24 data_path = os.path.dirname(os.path.realpath(__file__)) + "/demo_data" 25 pc_names = ["000700", "000750"] 26 NameError: name '__file__' is not defined for this data_path = os.path.dirname(os.path.realpath(__file__)) + "/demo_data" * Create LICENSE * add comments Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> Co-authored-by: YilingQiao <49262224+YilingQiao@users.noreply.github.com> Co-authored-by: ssheorey <41028320+ssheorey@users.noreply.github.com> Co-authored-by: Ignacio Vizzo <ignaciovizzo@gmail.com> Co-authored-by: prewettg <prewettg@gmail.com> Co-authored-by: Albhox <albertotono3@gmail.com> Co-authored-by: germanros1987 <38517452+germanros1987@users.noreply.github.com> * Fix broken link to torch RandLA-Net Toronto 3d model (#163) * Updating documentation (#154) * Editing documentation for TF and Torch dataloaders. * Updating datasets documentation * Updates after fixing style issues * Updating semantic segmentation * Updating dataset.py to fix semantic issues * Updating semantic segmentation * Updating base_dataset.py to fix semantic issues * Updating custom_dataset.py to fix semantic issues * Updating dataset.py to fix semantic issues * Updating visualizer documentation Updating files for visualizer documentation * Update customdataset.py * Fixing PR comment Fixing indentation issue * fix indent * Updating customdataset comments Updating customdataset to fix indentation issue. * Adding Jupyter tutorials Adding jupyter tutorials for: Training SS using PyTorch and Traing SS using TF * Update customdataset.py Fixing indentation issue. Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> * Add Tensorflow model and inference pipeline. (#159) * Fix missing argument * more import bugfixes (#126) * fix missing attribute 'utils' * removed import statements for unused modules * fix conflict * add kitti dataset * add readme about config files (#129) * readme about config files * link to predefined script * Update README.md * address reviews * Simplified install instructions (#127) * Simpliefied install instructions Multiple requirements files for different use cases. * minor change to README * minor change adding link to docs for build from source. * update install instruction, add +cpu to torch requirements.txt Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> * added conditionals in requirements-torch for macos (#131) * Fix color dictionary in Semantic-KITTI bgr -> rgb (#130) * Enable hierarchy UI feature in visualizer for SemanticKITTI (#133) * PointPillars port from mmdet without NMS and Voxelizer. Only inference. Focal loss and smooth L1 implemented and tested. * loss function implemented and tested * Add bounding boxes to visualizer * Voxelization layer for point_pillars * apply style * Dataset bounding boxes are now fully their own object and do hide auto-hide/show pieces associated with a geometry, but they do auto-hide irrelevant boxes when animating. * Style fixes * objdet metric * removed mmdet3d dependency, o3d nms and voxelizer added * renamed objdet to run_pipeline, implemented part of the objdet pipeline * Added documentation, changed definition of size argument to be edge-to-edge and adjusted code accordingly * kitti eval only 3d boxes * test pipeline point pillars * howto small fix * change bbox class * improve bbox * style * visualization of results * test vis of results * using new bounding box class * waymo bbox * added nuscenes bbox * added lyft bbox * apply style * anchor head refactoring * fix waymo bbox * fix kitti bbox * apply style; * removed transformation of the predicted boxes * added licenses to files * removed unnecessary parts * format * Labels displayed in visualization. Kitti dataset label ordering changed to match MMDetection3D. * added tf voxel class * added PFNlayer * add pillar feature net * added pointpillar scatter class * add class SECOND * added SECONDFPN layer * fix ragged tensor * implemented tf bbox generator, improved some torch helpers of pointpillars * batch support for box generation * add call method * fix name conflicts * fix bugs * added tf objdet pipeline * fix scatter tf * fix conv2d channels last * apply style * added crossentropy * add focal loss * added smooth L1 loss * apply style * fix batchnorm * add load/save ckpt * apply style * simplify inference torch * simplify inference tf * fix bug * fix ci * fix ci tf * apply style Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> Co-authored-by: YilingQiao <49262224+YilingQiao@users.noreply.github.com> Co-authored-by: ssheorey <41028320+ssheorey@users.noreply.github.com> Co-authored-by: Ignacio Vizzo <ignaciovizzo@gmail.com> Co-authored-by: prewettg <prewettg@gmail.com> Co-authored-by: Lukas Prantl <lukas_prantl@hotmail.de> Co-authored-by: lprantl <lprantl@lprantl-DESK.imu.intel.com> * Fixes for changes from TensorList to Tesor for t.geometry objects (#161) * Yiling/readme randlanet semantic3d (#167) * readme for randlanet semantic3d models * readme change * Prantl/point pillars train (#170) * Fix missing argument * more import bugfixes (#126) * fix missing attribute 'utils' * removed import statements for unused modules * fix conflict * add kitti dataset * add readme about config files (#129) * readme about config files * link to predefined script * Update README.md * address reviews * Simplified install instructions (#127) * Simpliefied install instructions Multiple requirements files for different use cases. * minor change to README * minor change adding link to docs for build from source. * update install instruction, add +cpu to torch requirements.txt Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> * added conditionals in requirements-torch for macos (#131) * Fix color dictionary in Semantic-KITTI bgr -> rgb (#130) * Enable hierarchy UI feature in visualizer for SemanticKITTI (#133) * PointPillars port from mmdet without NMS and Voxelizer. Only inference. Focal loss and smooth L1 implemented and tested. * loss function implemented and tested * Add bounding boxes to visualizer * Voxelization layer for point_pillars * apply style * Dataset bounding boxes are now fully their own object and do hide auto-hide/show pieces associated with a geometry, but they do auto-hide irrelevant boxes when animating. * Style fixes * objdet metric * removed mmdet3d dependency, o3d nms and voxelizer added * renamed objdet to run_pipeline, implemented part of the objdet pipeline * Added documentation, changed definition of size argument to be edge-to-edge and adjusted code accordingly * kitti eval only 3d boxes * test pipeline point pillars * howto small fix * change bbox class * improve bbox * style * visualization of results * test vis of results * using new bounding box class * waymo bbox * added nuscenes bbox * added lyft bbox * apply style * anchor head refactoring * fix waymo bbox * fix kitti bbox * apply style; * removed transformation of the predicted boxes * added licenses to files * removed unnecessary parts * format * Labels displayed in visualization. Kitti dataset label ordering changed to match MMDetection3D. * added tf voxel class * added PFNlayer * add pillar feature net * added pointpillar scatter class * add class SECOND * added SECONDFPN layer * fix ragged tensor * implemented tf bbox generator, improved some torch helpers of pointpillars * batch support for box generation * add call method * fix name conflicts * fix bugs * added tf objdet pipeline * fix scatter tf * fix conv2d channels last * apply style * added crossentropy * add focal loss * added smooth L1 loss * apply style * using our checkpoint format * fix batchnorm * add load/save ckpt * apply style * simplify inference torch * simplify inference tf * fix bug * fix ci * fix ci tf * apply style * implemented loss calculation of pointpillars, not yet tested * training working, evaluation and augmentation missing * fixed batched inference * style * new bev bounding box class * validation added * small fixes * small fix * reset yaw transformation in kitti bbox * fixed bug in loss calculation, fixed bug in save logs * removed debugging bug * fixed cls loss bug * style * Update kitti.py Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> Co-authored-by: YilingQiao <49262224+YilingQiao@users.noreply.github.com> Co-authored-by: ssheorey <41028320+ssheorey@users.noreply.github.com> Co-authored-by: Ignacio Vizzo <ignaciovizzo@gmail.com> Co-authored-by: prewettg <prewettg@gmail.com> Co-authored-by: lprantl <lprantl@lprantl-DESK.imu.intel.com> * Prantl/point pillars train tf (#171) * Fix missing argument * more import bugfixes (#126) * fix missing attribute 'utils' * removed import statements for unused modules * fix conflict * add kitti dataset * add readme about config files (#129) * readme about config files * link to predefined script * Update README.md * address reviews * Simplified install instructions (#127) * Simpliefied install instructions Multiple requirements files for different use cases. * minor change to README * minor change adding link to docs for build from source. * update install instruction, add +cpu to torch requirements.txt Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> * added conditionals in requirements-torch for macos (#131) * Fix color dictionary in Semantic-KITTI bgr -> rgb (#130) * Enable hierarchy UI feature in visualizer for SemanticKITTI (#133) * PointPillars port from mmdet without NMS and Voxelizer. Only inference. Focal loss and smooth L1 implemented and tested. * loss function implemented and tested * Add bounding boxes to visualizer * Voxelization layer for point_pillars * apply style * Dataset bounding boxes are now fully their own object and do hide auto-hide/show pieces associated with a geometry, but they do auto-hide irrelevant boxes when animating. * Style fixes * objdet metric * removed mmdet3d dependency, o3d nms and voxelizer added * renamed objdet to run_pipeline, implemented part of the objdet pipeline * Added documentation, changed definition of size argument to be edge-to-edge and adjusted code accordingly * kitti eval only 3d boxes * test pipeline point pillars * howto small fix * change bbox class * improve bbox * style * visualization of results * test vis of results * using new bounding box class * waymo bbox * added nuscenes bbox * added lyft bbox * apply style * anchor head refactoring * fix waymo bbox * fix kitti bbox * apply style; * removed transformation of the predicted boxes * added licenses to files * removed unnecessary parts * format * Labels displayed in visualization. Kitti dataset label ordering changed to match MMDetection3D. * added tf voxel class * added PFNlayer * add pillar feature net * added pointpillar scatter class * add class SECOND * added SECONDFPN layer * fix ragged tensor * implemented tf bbox generator, improved some torch helpers of pointpillars * batch support for box generation * add call method * fix name conflicts * fix bugs * added tf objdet pipeline * fix scatter tf * fix conv2d channels last * apply style * added crossentropy * add focal loss * added smooth L1 loss * apply style * using our checkpoint format * fix batchnorm * add load/save ckpt * apply style * simplify inference torch * simplify inference tf * fix bug * fix ci * fix ci tf * apply style * implemented loss calculation of pointpillars, not yet tested * training working, evaluation and augmentation missing * fixed batched inference * style * new bev bounding box class * validation added * small fixes * small fix * reset yaw transformation in kitti bbox * fixed bug in loss calculation, fixed bug in save logs * removed debugging bug * fixed cls loss bug * trainings pipeline for tensorflow * style * style * Update kitti.py * style Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> Co-authored-by: YilingQiao <49262224+YilingQiao@users.noreply.github.com> Co-authored-by: ssheorey <41028320+ssheorey@users.noreply.github.com> Co-authored-by: Ignacio Vizzo <ignaciovizzo@gmail.com> Co-authored-by: prewettg <prewettg@gmail.com> Co-authored-by: lprantl <lprantl@lprantl-DESK.imu.intel.com> * new validation for torch (#169) * infer * test and infer * testing * test inference * modify * before merge * inference dummy * add back save results * update model zoo (#175) * added weight initialization (#174) * Added ShapeNet dataset (#157) * Added ShapeNet dataset * Applied style * Added dummy part segmentation labels This is a hack as there aren't any official part labels (as far as I know). Co-authored-by: Matthias Humt <matthias.humt@dlr.de> Co-authored-by: germanros1987 <38517452+germanros1987@users.noreply.github.com> * Fix for changes in t::geometry (#173) * Add wide lines (#176) * Prantl/point pillars metrics (#172) * Fix missing argument * more import bugfixes (#126) * fix missing attribute 'utils' * removed import statements for unused modules * fix conflict * add kitti dataset * add readme about config files (#129) * readme about config files * link to predefined script * Update README.md * address reviews * Simplified install instructions (#127) * Simpliefied install instructions Multiple requirements files for different use cases. * minor change to README * minor change adding link to docs for build from source. * update install instruction, add +cpu to torch requirements.txt Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> * added conditionals in requirements-torch for macos (#131) * Fix color dictionary in Semantic-KITTI bgr -> rgb (#130) * Enable hierarchy UI feature in visualizer for SemanticKITTI (#133) * PointPillars port from mmdet without NMS and Voxelizer. Only inference. Focal loss and smooth L1 implemented and tested. * loss function implemented and tested * Add bounding boxes to visualizer * Voxelization layer for point_pillars * apply style * Dataset bounding boxes are now fully their own object and do hide auto-hide/show pieces associated with a geometry, but they do auto-hide irrelevant boxes when animating. * Style fixes * objdet metric * removed mmdet3d dependency, o3d nms and voxelizer added * renamed objdet to run_pipeline, implemented part of the objdet pipeline * Added documentation, changed definition of size argument to be edge-to-edge and adjusted code accordingly * kitti eval only 3d boxes * test pipeline point pillars * howto small fix * change bbox class * improve bbox * style * visualization of results * test vis of results * using new bounding box class * waymo bbox * added nuscenes bbox * added lyft bbox * apply style * anchor head refactoring * fix waymo bbox * fix kitti bbox * apply style; * removed transformation of the predicted boxes * added licenses to files * removed unnecessary parts * format * setup * Labels displayed in visualization. Kitti dataset label ordering changed to match MMDetection3D. * added temporary metric test + numba operators * added tf voxel class * added PFNlayer * add pillar feature net * added pointpillar scatter class * add class SECOND * added SECONDFPN layer * fix ragged tensor * add mAP metric * implemented tf bbox generator, improved some torch helpers of pointpillars * batch support for box generation * add call method * fix name conflicts * fix bugs * added tf objdet pipeline * fix scatter tf * fix conv2d channels last * apply style * added crossentropy * add focal loss * added smooth L1 loss * apply style * using our checkpoint format * fix batchnorm * add load/save ckpt * apply style * simplify inference torch * simplify inference tf * fix bug * fix ci * fix ci tf * fix ci * apply style * apply style * apply style * implemented loss calculation of pointpillars, not yet tested * changed list to tuple * training working, evaluation and augmentation missing * fixed batched inference * style * using same mAP technique as mmdet, 1 percent off * new bev bounding box class * validation added * small fixes * small fix * reset yaw transformation in kitti bbox * fixed bug in loss calculation, fixed bug in save logs * removed debugging bug * undone removing debug code for test run * old loader * some small fixes * cls loss fixed * undone changes in demo script * fixed cls loss bug * small bug fix in mAP calculation * metric bug fixes, o3d iou intergrated * trainings pipeline for tensorflow * fixed cumulative prediction calculation of mAP, no more deviation in mAP calculation, removed debugging code * mAP validation added to tf model * fixed convertion to eval data * small fixes * fixed infinite epoch * style * style * iou gpu/cpu depending on o3d build * Update kitti.py * replaced adamW with adam in tf training pipeline * removed legacy setup * style * fixed bug in loss computation of tf model, fixed bug in scatter operation of pointpillars tf * renamed tensorboard writer * tf summary writer * tf summary fix * mAP in tensorboard * fixed tf writer * fixed some merge artifacts Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> Co-authored-by: YilingQiao <49262224+YilingQiao@users.noreply.github.com> Co-authored-by: ssheorey <41028320+ssheorey@users.noreply.github.com> Co-authored-by: Ignacio Vizzo <ignaciovizzo@gmail.com> Co-authored-by: prewettg <prewettg@gmail.com> Co-authored-by: lprantl <lprantl@lprantl-DESK.imu.intel.com> * Filter kitti point cloud (#177) * reduce kitti pc * apply style * PointPillars bug fixes (#179) * fixed resuming from checkpoint * fixed offset in reassume * fixed missing device definition in pointpillars * Update object_detection.py removed debug log * Data Augmentation (#178) * shuffle * object range filter * add sample objects * added collect bbox * add box points in preprocessing * add object sample * add augment in config * bug fixes * apply style * remove duplicate * filter by min points * apply style * improve speed * fix tf * apply style * optional out_path * vectorization of points in shape, small bug fixes, removed pickle path Co-authored-by: praluk <lukas_prantl@hotmail.de> * fixed absolute path bug (#182) * Disable data augmentation while testing. (#181) * disable test augment * - validation without augmentation - transform returns bbox_obj - labels and bboxes single elements instead of list - fixed ignored min_points Co-authored-by: Lukas Prantl <lukas_prantl@hotmail.de> * update readme and config files for parislille3d; align points for parislille3d (#180) * randlanet parislille * config * merge * model path * minor changes * trans normalize * trans norm * fixed infinte dataset iteration (#184) * fixed infinte dataset iteration * - fixed obj det demo - preprocess full points * style * fix collision (#183) * Abhishek/documentation (#185) * Editing documentation for TF and Torch dataloaders. * Updating datasets documentation * Updates after fixing style issues * Updating semantic segmentation * Updating dataset.py to fix semantic issues * Updating semantic segmentation * Updating base_dataset.py to fix semantic issues * Updating custom_dataset.py to fix semantic issues * Updating dataset.py to fix semantic issues * Updating visualizer documentation Updating files for visualizer documentation * Update customdataset.py * Fixing PR comment Fixing indentation issue * fix indent * Updating customdataset comments Updating customdataset to fix indentation issue. * Adding Jupyter tutorials Adding jupyter tutorials for: Training SS using PyTorch and Traing SS using TF * Update customdataset.py Fixing indentation issue. * Updates to readme Added object detection updates to the readme.md in Open3D ML and Open3D ML\Script for the new release. * Update __init__.py * Fixing style errors Fixing style errors. Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> * In dataset mode, only bounding boxes from visible names are visible. Also update set_background_color() -> set_background() (#186) * Fix absolute path. (#187) * fix abs path * fix order of paths * fix skewed argoverse * Abhishek/documentation (#188) * Editing documentation for TF and Torch dataloaders. * Updating datasets documentation * Updates after fixing style issues * Updating semantic segmentation * Updating dataset.py to fix semantic issues * Updating semantic segmentation * Updating base_dataset.py to fix semantic issues * Updating custom_dataset.py to fix semantic issues * Updating dataset.py to fix semantic issues * Updating visualizer documentation Updating files for visualizer documentation * Update customdataset.py * Fixing PR comment Fixing indentation issue * fix indent * Updating customdataset comments Updating customdataset to fix indentation issue. * Adding Jupyter tutorials Adding jupyter tutorials for: Training SS using PyTorch and Traing SS using TF * Update customdataset.py Fixing indentation issue. * Updates to readme Added object detection updates to the readme.md in Open3D ML and Open3D ML\Script for the new release. * Update __init__.py * Fixing style errors Fixing style errors. * Updating Readme Updating readme to include image for visualization. * Replacing bounding_boxes image. Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> * Prantl/dataset fixes (#189) * - Object3D of datasets inherit from BEVBox, calib unified, output path of preprocessing scripts optional, label names instead of numbers * dataset configs * small bugfixes * fixes for Lyft training * added missing file * small bugfixes * added sample split * style * Update .gitignore * Fix Label LUT and Waymo (#190) * fix lut * fix waymo * address review * fixed style for mAP log in tf (#191) * Change the line width factor now that line widths are working (#192) * Prantl/pointpillars readme (#193) * updated pointpillar metrics * updated weights * object sampler fix (#194) * upload link (#195) Co-authored-by: Sanskar Agrawal <sanskaragrawal107@gmail.com> Co-authored-by: Benjamin Ummenhofer <benjaminum@gmail.com> Co-authored-by: YilingQiao <49262224+YilingQiao@users.noreply.github.com> Co-authored-by: ssheorey <41028320+ssheorey@users.noreply.github.com> Co-authored-by: Ignacio Vizzo <ignaciovizzo@gmail.com> Co-authored-by: prewettg <prewettg@gmail.com> Co-authored-by: Prantl <lukas_prantl@hotmail.de> Co-authored-by: lprantl <lprantl@lprantl-DESK.imu.intel.com> Co-authored-by: KENTO Yamamoto <31678561+kento-Y@users.noreply.github.com> Co-authored-by: Albhox <albertotono3@gmail.com> Co-authored-by: amirshal <35299570+amirshal@users.noreply.github.com> Co-authored-by: AbhishekS <65679171+ClarytyLLC@users.noreply.github.com> Co-authored-by: Matthias Humt <22399283+hummat@users.noreply.github.com> Co-authored-by: Matthias Humt <matthias.humt@dlr.de>