Add PPResNet from PaddleHub conversion (#4)

* add PPResNet impl and demo

* add benchmark impl and results for PPResNet

Author: fengyuentau

README.md

@@ -16,8 +16,8 @@ Hardware Setup:
 -->
 
 ***Important Notes***:
-- The time data that shown on the following tables presents the time elapsed from preprocess (resize is excluded), to a forward pass of a network, and postprocess to get final results.
-- The time data that shown on the following tables is the median of benchmark runs.
+- The time data that shown on the following table presents the time elapsed from preprocess (resize is excluded), to a forward pass of a network, and postprocess to get final results.
+- The time data that shown on the following table is the median of 10 runs. Different metrics may be applied to some specific models.
 - View [benchmark/config](./benchmark/config) for more details on benchmarking different models.
 
 <!--
@@ -33,6 +33,7 @@ Hardware Setup:
 | [DB](./models/text_detection_db)         | 640x480 | 137.38 | 2780.78 |
 | [CRNN](./models/text_recognition_crnn)   | 100x32  | 50.21  | 234.32  |
 | [SFace](./models/face_recognition_sface) | 112x112 | 8.69 | 96.79 |
+| [PP-ResNet](./models/image_classification_ppresnet) | 224x224 | 56.05 | 602.58
 
 
 ## License

benchmark/benchmark.py

@@ -75,6 +75,10 @@ def __init__(self, **kwargs):
         if self._use_label:
             self._labels = self._load_label()
 
+        self._to_rgb = kwargs.pop('toRGB', False)
+        self._resize = tuple(kwargs.pop('resize', []))
+        self._center_crop = kwargs.pop('centerCrop', None)
+
     def _load_label(self):
         labels = dict.fromkeys(self._files, None)
         for filename in self._files:
@@ -83,6 +87,19 @@ def _load_label(self):
 
     def __getitem__(self, idx):
         image = cv.imread(os.path.join(self._path, self._files[idx]))
+
+        if self._to_rgb:
+            image = cv.cvtColor(image, cv.COLOR_BGR2RGB)
+        if self._resize:
+            image = cv.resize(image, self._resize)
+        if self._center_crop:
+            h, w, _ = image.shape
+            w_crop = int((w - self._center_crop) / 2.)
+            assert w_crop >= 0
+            h_crop = int((h - self._center_crop) / 2.)
+            assert h_crop >= 0
+            image = image[w_crop:w-w_crop, h_crop:h-h_crop, :]
+
         if self._use_label:
             return self._files[idx], image, self._labels[self._files[idx]]
         else:
@@ -113,7 +130,10 @@ def forward(self, model, *args, **kwargs):
         if len(args) == 1:
             for size in self._sizes:
                 img_r = cv.resize(img, size)
-                model.setInputSize(size)
+                try:
+                    model.setInputSize(size)
+                except:
+                    pass
                 # TODO: batched inference
                 # input_data = [img] * self._batch_size
                 input_data = img_r
@@ -192,20 +212,21 @@ def build_from_cfg(cfg, registery):
     obj = registery.get(obj_name)
     return obj(**cfg)
 
-def prepend_pythonpath(cfg, key1, key2):
-    pythonpath = os.environ['PYTHONPATH']
-    if cfg[key1][key2].startswith('/'):
-        return
-    cfg[key1][key2] = os.path.join(pythonpath, cfg[key1][key2])
+def prepend_pythonpath(cfg):
+    for k, v in cfg.items():
+        if isinstance(v, dict):
+            prepend_pythonpath(v)
+        else:
+            if 'path' in k.lower():
+                cfg[k] = os.path.join(os.environ['PYTHONPATH'], v)
 
 if __name__ == '__main__':
     assert args.cfg.endswith('yaml'), 'Currently support configs of yaml format only.'
     with open(args.cfg, 'r') as f:
         cfg = yaml.safe_load(f)
 
     # prepend PYTHONPATH to each path
-    prepend_pythonpath(cfg['Benchmark'], key1='data', key2='path')
-    prepend_pythonpath(cfg, key1='Model', key2='modelPath')
+    prepend_pythonpath(cfg)
 
     # Instantiate benchmarking
     benchmark = Benchmark(**cfg['Benchmark'])

benchmark/config/image_classification_ppresnet.yaml

@@ -0,0 +1,20 @@
+Benchmark:
+  name: "Image Classification Benchmark"
+  data:
+    path: "benchmark/data/image_classification"
+    files: ["coffee_mug.jpg", "umbrella.jpg", "wall_clock.jpg"]
+    toRGB: True
+    resize: [256, 256]
+    centerCrop: 224
+  metric:
+    warmup: 3
+    repeat: 10
+    batchSize: 1
+    reduction: 'median'
+  backend: "default"
+  target: "cpu"
+
+Model:
+  name: "PPResNet"
+  modelPath: "models/image_classification_ppresnet/image_classification_ppresnet50.onnx"
+  labelPath: "models/image_classification_ppresnet/imagenet_labels.txt"

benchmark/download_data.py

@@ -173,6 +173,10 @@ def get_confirm_token(response):  # in case of large files
         url='https://drive.google.com/u/0/uc?id=1lTQdZUau7ujHBqp0P6M1kccnnJgO-dRj&export=download',
         sha='a40cf095ceb77159ddd2a5902f3b4329696dd866',
         filename='text.zip'),
+    image_classification=Downloader(name='image_classification',
+        url='https://drive.google.com/u/0/uc?id=1qcsrX3CIAGTooB-9fLKYwcvoCuMgjzGU&export=download',
+        sha='987546f567f9f11d150eea78951024b55b015401',
+        filename='image_classification.zip'),
 )
 
 if __name__ == '__main__':

models/__init__.py

@@ -2,6 +2,7 @@
 from .text_detection_db.db import DB
 from .text_recognition_crnn.crnn import CRNN
 from .face_recognition_sface.sface import SFace
+from .image_classification_ppresnet.ppresnet import PPResNet
 
 class Registery:
     def __init__(self, name):
@@ -18,4 +19,5 @@ def register(self, item):
 MODELS.register(YuNet)
 MODELS.register(DB)
 MODELS.register(CRNN)
-MODELS.register(SFace)
+MODELS.register(SFace)
+MODELS.register(PPResNet)

models/image_classification_ppresnet/LICENSE

@@ -0,0 +1,203 @@
+Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved
+
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+
+   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.

models/image_classification_ppresnet/README.md

@@ -0,0 +1,22 @@
+# ResNet
+
+Deep Residual Learning for Image Recognition
+
+This model is ported from [PaddleHub](https://github.com/PaddlePaddle/PaddleHub) using [this script from OpenCV](https://github.com/opencv/opencv/blob/master/samples/dnn/dnn_model_runner/dnn_conversion/paddlepaddle/paddle_resnet50.py).
+
+## Demo
+
+Run the following command to try the demo:
+```shell
+python demo.py --input /path/to/image
+```
+
+## License
+
+All files in this directory are licensed under [Apache 2.0 License](./LICENSE).
+
+## Reference
+
+- https://arxiv.org/abs/1512.03385
+- https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/paddlepaddle
+- https://github.com/PaddlePaddle/PaddleHub