I have spent 2 weeks to deploy the environment without success. Could you please pay for help to solve the problem? My email is [email protected] #93
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* fix (scale_factor): use new_tensor(scale_factor) in case it is numpy array * reformat (models): reformat with flake8, yapf, and isort to pass CI * fix (bbox_mapping): fix scale_factor bug in bbox_mapping * fix img_meta bug Co-authored-by: beansi <[email protected]>
* add new config sample and check scripts * context managere to prevent import * refactor backbone, add caffe * add fast rcnn * all basci config done * rm coco_proposal * add scratch, wider_face, voc * add reppoints * delete device id, auto resume * add libra_rcnn, ms_rcnn, nas_fpn * add hrnet, fcos * add free_anchor, gn, grid_rcnn, guided_anchoring, gcnet, ghm, gn+ws * finished all, but some need refactor and unified logic * fixed albu * update ReseNet101 * reduce ResNet101, add norm_cfg, 4conv1fc * refactor caffe backbone * merge act_cfg, dcn from master * rename 2fc head, add 4conv1fc head * delete 4con1fc model * rename components -> _base_ * flatten _base_ * refactor _base_ structure * refactor config structure * reduce _base/models * rename all config * add _coco inside configs * fixed _coco in files * fixed albu in test * migrate to new sys * fixed test * fixed test * rm cascade, fast_rcnn * rm cascade, fast_rcnn from _base_ * fixed fcos_center * rename from rule * collopse third party model * fixed test * fixed some minor bug * rename gn-neck_head -> gn-neck+head
* delete work_dir in all configs * add comment on work_dir priority
* add norm_eval * upgrade mmcv
* add unit tests for image loading * add test data * add a test case
* refactor resnet, add deep_stem and avg_down opt * move args into kwargs * add default * mv resnetv1d to resnet * fixed res_layer * add base_channels * add doc * add tests * update test * fixed backbone block conv_cfg/norm_cfg * add test * add tests
* create roi_head * create roi_head mv shared_head into roi_head * fix conflict * refactor(cascade rcnn): create cascade head in roi head, simplify cascade rcnn * type: fix scope: cascade_head subject: mv stage_loss_weight from train_cfg to roi_head creation * type: fix scope: roi_heads subject: handle the case when train_cfg is None * type: fix scope: roi_heads mask inference subject: fix test_cfg.rcnn bug to test_cfg * fix mask eval bug * refactor(double_head): refactor double head roi head * fix(double_head): clean code and fix __init__.py * refactor(mask scoring): create mask scoring roi head * refactor(htc_head): add htc_head * fix(htc_head): add htc_head in __init__.py * fix (htc_head): fix htc_head bugs * fix (ms_roi_head): rm test_cfg.rcnn to test_cfg * feature (grid rcnn): grid roi head * fix (grid_head): fix grid head bug * reformat and change all cfgs * reformat (roi_head): reformat __init__.py for isort=4.3.21 * fix roi_head test bug * fix (carafe): change carafe cfgs to use roi_head * fix (roi_head): fix missing roi_head refactor * reformat to pass CI * test all cfgs * match keys of configs with previous commit 77d073a * add and pass unittest for all roi heads * Refactor (roi_head): extract abstract base class for roi head * Refactor (roi_head): refactor init functions * Refactor (roi_head): weight init * Refactor (roi_head): add _bbox_forwrd & _mask_forward as basic functions * Fix (grid_roi_head): fix bug in bbox_forward_train * Refactor (roi_head): change to use img.device in forward_dummy) * Refactor (roi_heads): simplify init functions and _mask_forward * Fix (cascade_roi_head): fix init bug of cascade roi_head * Refactor (roi_head): use dict as outputs of _bbox_forward and _mask_forward * Refactor (test_config): scan valid configs rather than list them all
* refactor gcnet/emperical into plugin * add missing plugin * add docs, make plugins stage more flexible * refactor plugins into list[dict] * add duplicate test, update docs * update docs * update docs * update comment * update testbackbone doc
* Refactor (iou_assigner): set low quality match as an option * Fix (max_iou_assigner): fix typo and add clear detail * Fix (cascade_rcnn): set match_low_quality in cascade rcnn
* Feature (smooth-l1): support to use L1 loss * Refactor (L1-loss): Create a independent class for L1-loss * Refactor (l1-loss): add l1 loss in __init__ * Refactor (L1-loss): rm kwargs
* refactor mask structure * update and add comment * update test_config, add crop_and_resize * update to comment * add unittest * Update .travis.yml * add iter test * check mask type in albu Co-authored-by: Kai Chen <[email protected]>
* add CPU only mode which can be activated during install * fixed flake8 errors for too long lines, still have to deal with "import not at top of file" * reversing changes in MinIoURandomCrop, that not relevant to the CPU_ONLY pull request * moving the CPU_ONLY checks into deeper parts of the code * completing previous commit * using isort for imports sorting * yapf fix * followed @xvjiarui suggestions for the pull request * use mmdet.CPU_ONLY and replace the "--cpu" flag in setup.py with automatic check of cuda * make setup code cleaner * back to original implementation of MinIoURandomCrop * build all extensions with CUDA, if available * fixed DC * update doc * fixed masked_conv2d_ext * set warning once, update comment Co-authored-by: Yossi Biton <[email protected]> Co-authored-by: Yossi Biton <[email protected]>
* rename BitMap to Bitmap, add input check for polygon * fix test mask * fix test config * complete test * add mask contest test for bitmap resize * update with np.diag * perfect test polygon resize * perfect test polygon crop
* Refactor (all): change coordinate system * Fix (mask_head): fix cat -1 bug in mask_paste * Fix (unittest) : modify unittest and pass CI * reformat to pass CI * Fix round coordinates bugs * clean file * Fix (test): use cpu version of aligned roi_align in tests * Refactor (mask): clean np.stack * Refactor (head): reformat code and fix missing -1 * Reformat: reformat and add doc strings * Refactor (mask_head): more clea docstring
* Refactor (all): all category -1 in anchor/bbox head and anchor/bbox target assign * Fix (datasets): remove label + 1 in datasets * Fix (bbox_head): fix bug of fc_cls that forget + 1 * Fix (atss_head & free_anchor): fix cat -1 bugs * Fix (mask_head): remove label + 1 in mask heads * fix atss * Fix (rpn): fix cross_entropy_loss bug of RPN * Fix (anchor_head): fix typo * Refactor (anchor_head): use background_label rather than num_classes to indicate background class * Refactor (docstring): add and reformat docstrings * fix mask iou head * Fix (mask_head): fix cat -1 bug * Fix (mask_head): fix bug in mask inference * Add (tests): add tests for mask rcnn and mask heads * Refactor (unittest): refactor test_forward * Refactor (new_empty): use new_full rather than new_empty * Refactor (background_label): check background_label * Add TODO * Refactor (unittest): allow BP in unittest Co-authored-by: Cao Yuhang <[email protected]>
* add optimizer constructor * use format() instead of f-string to fix py3.5 errors * fix typo * update default optimizer constructor
* add sampler and assigner registry * rename with bbox prefix * restore __init__ * roll back atss_head * change import level * import from sampler/assigner
* speed inference of rpn * nms return sorted inds * add comment * minor perfect * rename idxs to inds
* add cfg for anchor head * add copy in two stage rpn
* add PAFPN * add doc * rename cfg, inherit from fpn * reformat doc string * standard doc string * fix doc of fpn * rename lateral_dconv to downsample_convs
* support-empty-tensor * minor update * add unit test * fix unit test * add assert value equal * simplify some codes * simplify unit tests * distinguish x with x_empty and x_normal * ref only forward once * fix python3.5 ci error
* rename api * Refactor (APIs): rename imgs_per_gpu to samples_per_gpu * Clean files * Refactor (infos): rename self.infos to self.data_infos
…… (#2410) * Refactor (training cfgs): change default training settings for better performance * Change RoIAlign sample num & caffe img norm * Refactor (LR): change 1/1000 to 0.001
* Add classes as input parameter * Update 'use my own datasets' documentation * Add test_datasets * Fix assert Co-authored-by: David de la Iglesia Castro <[email protected]>
* fix gcc requirement * move gcc requirement to install.md
* Add regression test * Fix with copy img * Revert "Fix with copy img" This reverts commit 86f07e89a400d3cf73464374c7d1ef3d85649c8e. * Move test to `test_transform`
* fix async test * minor fix
* update model_zoo url * update mmcv version requirement
* Add cls weight in CrossEntropyLoss * update unittes * resolve comments * fix unittest bug
* add 3x link * Update model links * clean scripts * fix typo
* fix a typo * fix another typo in comment
* Update links * clean empty link
* add tutorials * use arxiv page
fixing link typos
* Add upsample_cfg support in FPN * small fix * Add multiple extra conv sources * small logical fix * Add neck tests for fpn * Add neck tests for fpn * fixed several typos * resolved issues * Removed extra_convs_source option * added necks to apis.rst * change according to comments * add bbox_fields to expand and min iou crop * reconfigured configs * small fix * added test for random crop and min iou random crop * small change * added valid_inds for masks in random crop according to #2802 * added config unit test * deleted nas fpn config test * revise according to comments * add img_fields check in transform.py and test_transform.py * Added notes for random crop and min iou random crop * Added notes for random crop and min iou random crop * Add bbox2label and bbox2mask key correspondence * Update nas-fpn model Add fsaf log
* add lvis dataset * fixed eval * fixed test cfg * add resnext config * update md * fixed name * update model urls * minor fix * fixed typo * use open-mmlab lvis * update travis * fixed install * make class balance as default
* add dcn offset doc * move to doc string
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thanks