diff --git a/models/public/efficientdet-d0-tf/accuracy-check.yml b/models/public/efficientdet-d0-tf/accuracy-check.yml new file mode 100644 index 00000000000..2c0b8747733 --- /dev/null +++ b/models/public/efficientdet-d0-tf/accuracy-check.yml @@ -0,0 +1,23 @@ +models: + - name: efficientdet-d0-tf + launchers: + - framework: dlsdk + adapter: ssd + datasets: + - name: ms_coco_detection_90_class_without_backgound + preprocessing: + - type: resize + aspect_ratio_scale: fit_to_window + size: 512 + - type: padding + size: 512 + pad_type: right_bottom + + postprocessing: + - type: faster_rcnn_postprocessing_resize + size: 512 + - type: shift_labels + offset: 1 + + metrics: + - type: coco_precision diff --git a/models/public/efficientdet-d0-tf/efficientdet-d0-tf.md b/models/public/efficientdet-d0-tf/efficientdet-d0-tf.md new file mode 100644 index 00000000000..364c0f226ee --- /dev/null +++ b/models/public/efficientdet-d0-tf/efficientdet-d0-tf.md @@ -0,0 +1,86 @@ +# efficientdet-d0-tf + +## Use Case and High-Level Description + +The "efficientdet-d0" model is one of the [EfficientDet](https://arxiv.org/abs/1911.09070) +models designed to perform object detection. This model was pretrained in TensorFlow*. +All the EfficientDet models have been pretrained on the MSCOCO* image database. +For details about this family of models, check out the Google AutoML [repository] +(https://github.com/google/automl/tree/master/efficientdet). + +## Example + +## Specification + +| Metric | Value | +|-------------------|-----------------| +| Type | Object detection| +| GFLOPs | 0.819 | +| MParams | 5.268 | +| Source framework | TensorFlow\* | + +## Accuracy + +| Metric | Converted model | +| ------ | --------------- | +| coco_precision | 31.95%| + +## Performance + +## Input + +### Original Model + +Image, name - `convert_image/Cast`, shape - `[1x512x512x3]`, format is `[BxHxWxC]`, where: + +- `B` - batch size +- `H` - height +- `W` - width +- `C` - channel + +Channel order is `RGB`. + +### Converted Model + +Image, name - `convert_image/Cast/placeholder_port_0`, shape - `[1x3x512x512]`, format is `[BxCxHxW]`, where: + +- `B` - batch size +- `C` - channel +- `H` - height +- `W` - width + +Channel order is `BGR`. + +## Output + +### Original Model + +The array of summary detection information, name: `detections`, shape: [1, 7, N], where N is the number of detected +bounding boxes. For each detection, the description has the format: +[`image_id`, `y_min`, `x_min`, `y_max`, `x_max`, `confidence`, `label`], + where: + + - `image_id` - ID of the image in the batch + - (`x_min`, `y_min`) - coordinates of the top left bounding box corner + - (`x_max`, `y_max`) - coordinates of the bottom right bounding box corner + - `confidence` - confidence for the predicted class + - `label` - predicted class ID, starting from 1 + +### Converted Model + +The array of summary detection information, name: `detections`, shape: [1, 1, N, 7], where N is the number of detected +bounding boxes. For each detection, the description has the format: +[`image_id`, `label`, `conf`, `x_min`, `y_min`, `x_max`, `y_max`], + where: + + - `image_id` - ID of the image in the batch + - `label` - predicted class ID, starting from 0 + - `conf` - confidence for the predicted class + - (`x_min`, `y_min`) - coordinates of the top left bounding box corner (coordinates stored in normalized format, in range [0, 1]) + - (`x_max`, `y_max`) - coordinates of the bottom right bounding box corner (coordinates stored in normalized format, in range [0, 1]) + +## Legal Information + +The original model is distributed under the +[Apache License, Version 2.0](https://raw.githubusercontent.com/google/automl/master/LICENSE). +A copy of the license is provided in [APACHE-2.0-TF-AutoML.txt](../licenses/APACHE-2.0-TF-AutoML.txt). diff --git a/models/public/efficientdet-d0-tf/model.yml b/models/public/efficientdet-d0-tf/model.yml new file mode 100644 index 00000000000..d325b1ba7b0 --- /dev/null +++ b/models/public/efficientdet-d0-tf/model.yml @@ -0,0 +1,113 @@ +# Copyright (c) 2020 Intel Corporation +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +description: >- + The "efficientdet-d0" model is one of the EfficientDet + models designed to perform object detection. This model was pretrained in TensorFlow*. + All the EfficientDet models have been pretrained on the MSCOCO* image database. + For details about this family of models, check out the Google AutoML repository + . +task_type: detection +files: + - name: efficientdet-d0.tar.gz + size: 28828936 + sha256: 74794c937aa1fa2f559c2393d22b251b1f7135a49b108bd0414bc4f4800ca15d + source: https://storage.googleapis.com/cloud-tpu-checkpoints/efficientdet/coco2/efficientdet-d0.tar.gz + - name: model_inspect.py + size: 20388 + sha256: 6c68fe02f10d62dd87c2fc550b41c3df5cce52f0449be22e0699fbf209e3cbc1 + source: https://raw.githubusercontent.com/google/automl/341af7d4da7805c3a874877484e133f33c420ec5/efficientdet/model_inspect.py + - name: hparams_config.py + size: 13750 + sha256: a7f9a3215a864e2f393addefc997ceba1d78ccba4909390310c453e391c9710b + source: https://raw.githubusercontent.com/google/automl/341af7d4da7805c3a874877484e133f33c420ec5/efficientdet/hparams_config.py + - name: inference.py + size: 25076 + sha256: 1f0a633de186f9b786979ead00921b910e9853bb33717328f76c1f71af8be997 + source: https://raw.githubusercontent.com/google/automl/341af7d4da7805c3a874877484e133f33c420ec5/efficientdet/inference.py + - 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$type: regex_replace + file: keras/anchors.py + pattern: 'from object_detection' + replacement: '# \g<0>' + + - $type: unpack_archive + format: gztar + file: efficientdet-d0.tar.gz +model_optimizer_args: + - --input_shape=[1,512,512,3] + - --input=convert_image/Cast + - --reverse_input_channels + - --input_model=$conv_dir/efficientdet-d0_saved_model/efficientdet-d0_frozen.pb + - --output=concat,concat_1 + - --transformations_config=$mo_dir/extensions/front/tf/automl_efficientdet.json +framework: tf +license: https://raw.githubusercontent.com/google/automl/master/LICENSE diff --git a/models/public/efficientdet-d0-tf/pre-convert.py b/models/public/efficientdet-d0-tf/pre-convert.py new file mode 100644 index 00000000000..4e2d87671dd --- /dev/null +++ b/models/public/efficientdet-d0-tf/pre-convert.py @@ -0,0 +1,38 @@ +#!/usr/bin/env python3 + +# Copyright (c) 2020 Intel Corporation +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import subprocess +import sys + +from pathlib import Path + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument('input_dir', type=Path) + parser.add_argument('output_dir', type=Path) + args = parser.parse_args() + + subprocess.run([sys.executable, '--', + str(args.input_dir / 'model_inspect.py'), + "--runmode=saved_model", + "--model_name=efficientdet-d0", + "--ckpt_path={}".format(args.input_dir / "efficientdet-d0"), + "--saved_model_dir={}".format(args.output_dir / "efficientdet-d0_saved_model") + ], check=True) + +if __name__ == '__main__': + main() diff --git a/models/public/efficientdet-d1-tf/accuracy-check.yml b/models/public/efficientdet-d1-tf/accuracy-check.yml new file mode 100644 index 00000000000..ac9c8bbcb29 --- /dev/null +++ b/models/public/efficientdet-d1-tf/accuracy-check.yml @@ -0,0 +1,23 @@ +models: + - name: efficientdet-d1-tf + launchers: + - framework: dlsdk + adapter: ssd + datasets: + - name: ms_coco_detection_90_class_without_backgound + preprocessing: + - type: resize + aspect_ratio_scale: fit_to_window + size: 640 + - type: padding + size: 640 + pad_type: right_bottom + + postprocessing: + - type: faster_rcnn_postprocessing_resize + size: 640 + - type: shift_labels + offset: 1 + + metrics: + - type: coco_precision diff --git a/models/public/efficientdet-d1-tf/efficientdet-d1-tf.md b/models/public/efficientdet-d1-tf/efficientdet-d1-tf.md new file mode 100644 index 00000000000..6905250d55d --- /dev/null +++ b/models/public/efficientdet-d1-tf/efficientdet-d1-tf.md @@ -0,0 +1,86 @@ +# efficientdet-d1-tf + +## Use Case and High-Level Description + +The "efficientdet-d1" model is one of the [EfficientDet](https://arxiv.org/abs/1911.09070) +models designed to perform object detection. This model was pretrained in TensorFlow*. +All the EfficientDet models have been pretrained on the MSCOCO* image database. +For details about this family of models, check out the Google AutoML [repository] +(https://github.com/google/automl/tree/master/efficientdet). + +## Example + +## Specification + +| Metric | Value | +|-------------------|-----------------| +| Type | Object detection| +| GFLOPs | 0.819 | +| MParams | 5.268 | +| Source framework | TensorFlow\* | + +## Accuracy + +| Metric | Converted model | +| ------ | --------------- | +| coco_precision | 37.54%| + +## Performance + +## Input + +### Original Model + +Image, name - `convert_image/Cast`, shape - `[1x640x640x3]`, format is `[BxHxWxC]`, where: + +- `B` - batch size +- `H` - height +- `W` - width +- `C` - channel + +Channel order is `RGB`. + +### Converted Model + +Image, name - `convert_image/Cast/placeholder_port_0`, shape - `[1x3x640x640]`, format is `[BxCxHxW]`, where: + +- `B` - batch size +- `C` - channel +- `H` - height +- `W` - width + +Channel order is `BGR`. + +## Output + +### Original Model + +The array of summary detection information, name: `detections`, shape: [1, 7, N], where N is the number of detected +bounding boxes. For each detection, the description has the format: +[`image_id`, `y_min`, `x_min`, `y_max`, `x_max`, `confidence`, `label`], + where: + + - `image_id` - ID of the image in the batch + - (`x_min`, `y_min`) - coordinates of the top left bounding box corner + - (`x_max`, `y_max`) - coordinates of the bottom right bounding box corner + - `confidence` - confidence for the predicted class + - `label` - predicted class ID, starting from 1 + +### Converted Model + +The array of summary detection information, name: `detections`, shape: [1, 1, N, 7], where N is the number of detected +bounding boxes. For each detection, the description has the format: +[`image_id`, `label`, `conf`, `x_min`, `y_min`, `x_max`, `y_max`], + where: + + - `image_id` - ID of the image in the batch + - `label` - predicted class ID, starting from 0 + - `conf` - confidence for the predicted class + - (`x_min`, `y_min`) - coordinates of the top left bounding box corner (coordinates stored in normalized format, in range [0, 1]) + - (`x_max`, `y_max`) - coordinates of the bottom right bounding box corner (coordinates stored in normalized format, in range [0, 1]) + +## Legal Information + +The original model is distributed under the +[Apache License, Version 2.0](https://raw.githubusercontent.com/google/automl/master/LICENSE). +A copy of the license is provided in [APACHE-2.0-TF-AutoML.txt](../licenses/APACHE-2.0-TF-AutoML.txt). diff --git a/models/public/efficientdet-d1-tf/model.yml b/models/public/efficientdet-d1-tf/model.yml new file mode 100644 index 00000000000..ac012739e98 --- /dev/null +++ b/models/public/efficientdet-d1-tf/model.yml @@ -0,0 +1,113 @@ +# Copyright (c) 2020 Intel Corporation +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +description: >- + The "efficientdet-d1" model is one of the EfficientDet + models designed to perform object detection. This model was pretrained in TensorFlow*. + All the EfficientDet models have been pretrained on the MSCOCO* image database. + For details about this family of models, check out the Google AutoML repository + . +task_type: detection +files: + - name: efficientdet-d1.tar.gz + size: 48828228 + sha256: 31d8741da9840ab8bddfaa041d395d84a8c1e4e54db01cf8d277471afad5d6e0 + source: https://storage.googleapis.com/cloud-tpu-checkpoints/efficientdet/coco2/efficientdet-d1.tar.gz + - name: model_inspect.py + size: 20388 + sha256: 6c68fe02f10d62dd87c2fc550b41c3df5cce52f0449be22e0699fbf209e3cbc1 + source: https://raw.githubusercontent.com/google/automl/341af7d4da7805c3a874877484e133f33c420ec5/efficientdet/model_inspect.py + - name: hparams_config.py + size: 13750 + sha256: a7f9a3215a864e2f393addefc997ceba1d78ccba4909390310c453e391c9710b + source: https://raw.githubusercontent.com/google/automl/341af7d4da7805c3a874877484e133f33c420ec5/efficientdet/hparams_config.py + - name: inference.py + size: 25076 + sha256: 1f0a633de186f9b786979ead00921b910e9853bb33717328f76c1f71af8be997 + source: https://raw.githubusercontent.com/google/automl/341af7d4da7805c3a874877484e133f33c420ec5/efficientdet/inference.py + - 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$type: regex_replace + file: keras/anchors.py + pattern: 'from object_detection' + replacement: '# \g<0>' + + - $type: unpack_archive + format: gztar + file: efficientdet-d1.tar.gz +model_optimizer_args: + - --input_shape=[1,640,640,3] + - --input=convert_image/Cast + - --reverse_input_channels + - --input_model=$conv_dir/efficientdet-d1_saved_model/efficientdet-d1_frozen.pb + - --output=concat,concat_1 + - --transformations_config=$mo_dir/extensions/front/tf/automl_efficientdet.json +framework: tf +license: https://raw.githubusercontent.com/google/automl/master/LICENSE diff --git a/models/public/efficientdet-d1-tf/pre-convert.py b/models/public/efficientdet-d1-tf/pre-convert.py new file mode 100644 index 00000000000..e32d9b6c275 --- /dev/null +++ b/models/public/efficientdet-d1-tf/pre-convert.py @@ -0,0 +1,38 @@ +#!/usr/bin/env python3 + +# Copyright (c) 2020 Intel Corporation +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import subprocess +import sys + +from pathlib import Path + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument('input_dir', type=Path) + parser.add_argument('output_dir', type=Path) + args = parser.parse_args() + + subprocess.run([sys.executable, '--', + str(args.input_dir / 'model_inspect.py'), + "--runmode=saved_model", + "--model_name=efficientdet-d1", + "--ckpt_path={}".format(args.input_dir / "efficientdet-d1"), + "--saved_model_dir={}".format(args.output_dir / "efficientdet-d1_saved_model") + ], check=True) + +if __name__ == '__main__': + main() diff --git a/models/public/index.md b/models/public/index.md index 58e0af3990e..f8a1a59ad28 100644 --- a/models/public/index.md +++ b/models/public/index.md @@ -111,6 +111,8 @@ SSD-based and provide reasonable accuracy/performance trade-offs. | CTPN | TensorFlow\* | [ctpn](./ctpn/ctpn.md) | 73.67% | 55.813 | 17.237 | | CenterNet (CTDET with DLAV0) 384x384 | ONNX\* | [ctdet_coco_dlav0_384](./ctdet_coco_dlav0_384/ctdet_coco_dlav0_384.md)| 41.6105%| 34.994 | 17.911 | | CenterNet (CTDET with DLAV0) 512x512 | ONNX\* | [ctdet_coco_dlav0_512](./ctdet_coco_dlav0_512/ctdet_coco_dlav0_512.md)| 44.2756%| 62.211 | 17.911 | +| EfficientDet-D0 | TensorFlow\* | [efficientdet-d0-tf](./efficientdet-d0-tf/efficientdet-d0-tf.md)| 31.95% | | | +| EfficientDet-D1 | TensorFlow\* | [efficientdet-d1-tf](./efficientdet-d1-tf/efficientdet-d1-tf.md)| 37.54% | | | | FaceBoxes | PyTorch\* | [faceboxes-pytorch](./faceboxes-pytorch/faceboxes-pytorch.md)|83.565% | 1.8975 | 1.0059 | | Faster R-CNN with Inception-ResNet v2| TensorFlow\* | [faster_rcnn_inception_resnet_v2_atrous_coco](./faster_rcnn_inception_resnet_v2_atrous_coco/faster_rcnn_inception_resnet_v2_atrous_coco.md)| 36.76%/52.41% | 30.687 | 13.307 | | Faster R-CNN with Inception v2 | TensorFlow\* | [faster_rcnn_inception_v2_coco](./faster_rcnn_inception_v2_coco/faster_rcnn_inception_v2_coco.md) | 25.65%/40.04%| 30.687 | 13.307 | diff --git a/models/public/licenses/APACHE-2.0-TF-AutoML.txt b/models/public/licenses/APACHE-2.0-TF-AutoML.txt new file mode 100644 index 00000000000..c5101efccb3 --- /dev/null +++ b/models/public/licenses/APACHE-2.0-TF-AutoML.txt @@ -0,0 +1,203 @@ +Copyright 2020 Google Research. 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