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Update repo #9

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Update repo #9

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martinruenz and others added 30 commits October 24, 2018 17:37
Fix a small typo
It is simpler and requires less effort (i.e. no auth) compared to SSH
Access repos via https in INSTALL.md
* Add missing __init__.py files

* Add packages

* Rename logging.py to logger.py

Import rules from Python2 makes this a bad idea

* Make import_file py2 compatible

* list does not have .copy() in py2

* math.log2 does not exist in py2

* Miscellaneous fixes for py2

* Address comments
Fix BoxList constructor call in README.md
Replace baseline with benchmark
Replace BoxList argument size with image_size.
use cuda version torch.randperm to avoid copy from gpu to cpu and a fatal bug in multi-thread cpu version
* quick fix for area

* Update bounding_box.py
## Bug
When I repeatedly invoke build_detection_model function to build the model, I will get the error: `AttributeError: 'ResNet' object has no attribute 'layer1'`. 

## To Reproduce
```
model = build_detection_model(cfg)
model = build_detection_model(cfg)
```

## The reason
The variable `ResNet50StagesTo4` is a global generator expression, so when we build the model secondly, the code executes to Line 82 `for stage_spec in stage_specs:` and `stage_specs` will return empty leading to do not add any stage. Finally, `self._freeze_backbone` try to freeze the backbone by executing `m = getattr(self, "layer" + str(stage_index))` firstly. At the moment, it will throw the AttributeError `AttributeError: 'ResNet' object has no attribute 'layer1'`.

I guess you want to define ResNet50StagesTo4 as the tuple, so I try to fix by add tuple type qualifier.

## The solution
Add the tuple type to `ResNet50StagesTo5`, `ResNet50StagesTo4`, `ResNet50FPNStagesTo5`, `ResNet101FPNStagesTo5`.

I do not know whether there are similar bug existing, so you need to review my solution. Thank you!
* added Dockerfile

* intructions for installation with docker

* adds nccl to dockerfile

* Update Dockerfile

* Update INSTALL.md
* adding registry to hook custom building blocks

* adding customizable rpn head

* support customizable c2 weight loading
botcs and others added 26 commits September 16, 2019 07:43
…gamma_alpha

gamma, alpha are supposed to be floats, delete lines with [0] subscripts   #1013
install local pip with conda
Add uncompressed rle condition in Binarymask
remove redundant reshape of box_regression
Update lr scheduling to pytorch 1.1.0
Validation during training (version 2)
replacing dtype torch.uint8 with torch.bool for indexing in pytorch 1.2.0
Add native CityScapes evaluation tool
Extend COCO evaluation for AbstractDataset
bugfix: use correct config for tta and device handling during inference
Move horizontal flip probability to config
add the MULAN project in readme.MD, "Projects using maskrcnn-benchmark"
Thanks for your excellent work! @fmassa 
Based on this repository, we research on the object detectors without sampling heuristics (e.g., Focal Loss, GHM, Undersampling).
The paper (https://arxiv.org/abs/1909.04868) and code (https://github.com/ChenJoya/sampling-free) have been released. Thank you again for maskrcnn-benchmark. It is a really simple, efficient, high performance object detection benchmark.
haofengac pushed a commit that referenced this pull request Nov 30, 2019
Fix a small typo
@facebook-github-bot facebook-github-bot deleted the branch haofengac:master September 1, 2021 11:41
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