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Commit c41d6565 authored by A. Unique TensorFlower's avatar A. Unique TensorFlower
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# TF-Vision Model Garden # TF-Vision Model Garden
⚠️ Disclaimer: All datasets hyperlinked from this page are not owned or
distributed by Google. The dataset is made available by third parties.
Please review the terms and conditions made available by the third parties
before using the data.
## Introduction ## Introduction
TF-Vision modeling library for computer vision provides a collection of TF-Vision modeling library for computer vision provides a collection of
...@@ -59,11 +64,12 @@ depth, label smoothing and dropout. ...@@ -59,11 +64,12 @@ depth, label smoothing and dropout.
* [RetinaNet](https://arxiv.org/abs/1708.02002) and [RetinaNet-RS](https://arxiv.org/abs/2107.00057) * [RetinaNet](https://arxiv.org/abs/1708.02002) and [RetinaNet-RS](https://arxiv.org/abs/2107.00057)
* [Mask R-CNN](https://arxiv.org/abs/1703.06870) * [Mask R-CNN](https://arxiv.org/abs/1703.06870)
* [Cascade RCNN](https://arxiv.org/abs/1712.00726) and [Cascade RCNN-RS](https://arxiv.org/abs/2107.00057) * [Cascade RCNN](https://arxiv.org/abs/1712.00726) and [Cascade RCNN-RS](https://arxiv.org/abs/2107.00057)
* Models are all trained on [COCO](https://cocodataset.org/) train2017 and
* Models are all trained on COCO train2017 and evaluated on COCO val2017. evaluated on [COCO](https://cocodataset.org/) val2017.
* Training details: * Training details:
* Models finetuned from ImageNet pretrained checkpoints adopt the 12 or 36 * Models finetuned from [ImageNet](https://www.image-net.org/) pretrained
epochs schedule. Models trained from scratch adopt the 350 epochs schedule. checkpoints adopt the 12 or 36 epochs schedule. Models trained from scratch
adopt the 350 epochs schedule.
* The default training data augmentation implements horizontal flipping and * The default training data augmentation implements horizontal flipping and
scale jittering with a random scale between [0.5, 2.0]. scale jittering with a random scale between [0.5, 2.0].
* Unless noted, all models are trained with l2 weight regularization and ReLU * Unless noted, all models are trained with l2 weight regularization and ReLU
...@@ -106,18 +112,18 @@ depth, label smoothing and dropout. ...@@ -106,18 +112,18 @@ depth, label smoothing and dropout.
| Backbone | Resolution | Epochs | FLOPs (B) | Params (M) | Box AP | Mask AP | Download | | Backbone | Resolution | Epochs | FLOPs (B) | Params (M) | Box AP | Mask AP | Download |
| ------------ |:-------------:| -------:|-----------:|-----------:|-------:|--------:|---------:| | ------------ |:-------------:| -------:|-----------:|-----------:|-------:|--------:|---------:|
ResNet50-FPN | 640x640 | 350 | 227.7 | 46.3 | 42.3 | 37.6 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/r50fpn_640_coco_scratch_tpu4x4.yaml) | | ResNet50-FPN | 640x640 | 350 | 227.7 | 46.3 | 42.3 | 37.6 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/r50fpn_640_coco_scratch_tpu4x4.yaml) |
| SpineNet-49 | 640x640 | 350 | 215.7 | 40.8 | 42.6 | 37.9 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet49_mrcnn_tpu.yaml) | | SpineNet-49 | 640x640 | 350 | 215.7 | 40.8 | 42.6 | 37.9 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet49_mrcnn_tpu.yaml) |
SpineNet-96 | 1024x1024 | 500 | 315.0 | 55.2 | 48.1 | 42.4 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet96_mrcnn_tpu.yaml) | | SpineNet-96 | 1024x1024 | 500 | 315.0 | 55.2 | 48.1 | 42.4 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet96_mrcnn_tpu.yaml) |
SpineNet-143 | 1280x1280 | 500 | 498.8 | 79.2 | 49.3 | 43.4 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet143_mrcnn_tpu.yaml) | | SpineNet-143 | 1280x1280 | 500 | 498.8 | 79.2 | 49.3 | 43.4 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet143_mrcnn_tpu.yaml) |
#### Cascade RCNN-RS (Trained from scratch) #### Cascade RCNN-RS (Trained from scratch)
backbone | resolution | epochs | params (M) | box AP | mask AP | download | Backbone | Resolution | Epochs | Params (M) | Box AP | Mask AP | Download
------------ | :--------: | -----: | ---------: | -----: | ------: | -------: ------------ | :--------: | -----: | ---------: | -----: | ------: | -------:
SpineNet-49 | 640x640 | 500 | 56.4 | 46.4 | 40.0 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet49_cascadercnn_tpu.yaml)| | SpineNet-49 | 640x640 | 500 | 56.4 | 46.4 | 40.0 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet49_cascadercnn_tpu.yaml)|
SpineNet-143 | 1280x1280 | 500 | 94.9 | 51.9 | 45.0 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet143_cascadercnn_tpu.yaml)| | SpineNet-143 | 1280x1280 | 500 | 94.9 | 51.9 | 45.0 | [config](https://github.com/tensorflow/models/blob/master/official/vision/beta/configs/experiments/maskrcnn/coco_spinenet143_cascadercnn_tpu.yaml)|
## Semantic Segmentation ## Semantic Segmentation
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