# D2Go Model Zoo and Baselines ## Introduction This page holds a reference for example configs, pretrained models and training/evaluation metrics. You can access these models from code using d2go.model_zoo API. ### How to - Get pretrained models in python: ```python from d2go.model_zoo import model_zoo model = model_zoo.get('faster_rcnn_fbnetv3a_C4.yaml', trained=True) ``` - Train: the "name" column contains a link to the config file. Running `d2go.train_net --config-file` with the config file will reproduce the corresponding model. - Evaluation: Running `d2go.train_net --config-file path/to/the/config --eval-only MODEL.WEIGHTS path/to/the/model/weights` with the config file and pretrained model will evaluate the results. See details in [Getting Started](./demo/README.md). - Training curves and other statistics can be found in `metrics` for each model. ### Backbone Models FBNet series are efficient mobile backbones discovered via neural architecture search, which are specially optimized for mobile devices. Please see details in the [paper](https://arxiv.org/pdf/2006.02049.pdf). If using our code/models in your research, please cite our paper: ``` @article{dai2020fbnetv3, title={FBNetV3: Joint architecture-recipe search using neural acquisition function}, author={Dai, Xiaoliang and Wan, Alvin and Zhang, Peizhao and Wu, Bichen and He, Zijian and Wei, Zhen and Chen, Kan and Tian, Yuandong and Yu, Matthew and Vajda, Peter and others}, journal={arXiv preprint arXiv:2006.02049}, year={2020} } ``` ## COCO Object Detection | name | box AP | latency* | model id | download | | ------------------------------------------------------------ | ------ | ------- | --------- | ------------------------------------------------------------ | | [Faster-RCNN-FBNetV3A](./configs/faster_rcnn_fbnetv3a_C4.yaml) | 22.99 | 73.3ms | 246823121 | [model](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/246823121/model_0479999.pth) \|[metrics](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/246823121/metrics.json) | | [Faster-RCNN-FBNetV3A-dsmask](./configs/faster_rcnn_fbnetv3a_dsmask_C4.yaml) | 21.06 | 33.7ms | 250414811 | [model](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/250414811/model_0399999.pth) \|[metrics](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/250414811/metrics.json) | | [Faster-RCNN-FBNetV3G-FPN](./configs/faster_rcnn_fbnetv3g_fpn.yaml) | 43.13 | - | 250356938 | [model](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/250356938/model_0374999.pth) \|[metrics](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/250356938/metrics.json) | *: tested on Samsung Galaxy S8 with quantization ## COCO Instance Segmentation | name | box AP | mask AP | model id | download | | ------------------------------------------------------------ | ------ | ------- | --------- | ------------------------------------------------------------ | | [Mask-RCNN-FBNetV3A](./configs/mask_rcnn_fbnetv3a_C4.yaml) | 23.05 | 20.71 | 268421013 | [model](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/268421013/model_final.pth) \|[metrics](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/268421013/metrics.json) | | [Mask-RCNN-FBNetV3A-dsmask](./configs/mask_rcnn_fbnetv3a_dsmask_C4.yaml) | 21.76 | 19.97 | 268412271 | [model](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/268412271/model_0499999.pth) \|[metrics](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/268412271/metrics.json) | | [Mask-RCNN-FBNetV3G-FPN](./configs/mask_rcnn_fbnetv3g_fpn.yaml) | 43.31 | 39.24 | 287445123 | [model](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/287445123/model_0409999.pth) \|[metrics](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/287445123/metrics.json) | ### COCO Person Keypoint Detection | name | box AP | kp. AP | model id | download | | ------------------------------------------------------------ | ------ | ------ | --------- | ------------------------------------------------------------ | | [Keypoint-RCNN-FBNetV3A-dsmask](./configs/keypoint_rcnn_fbnetv3a_dsmask_C4.yaml) | 31.24 | 35.56 | 250430934 | [model](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/250430934/model_0389999.pth) \|[metrics](https://mobile-cv.s3-us-west-2.amazonaws.com/d2go/models/250430934/metrics.json) |