diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/LICENSE b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..261eeb9e9f8b2b4b0d119366dda99c6fd7d35c64 --- /dev/null +++ b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/LICENSE @@ -0,0 +1,201 @@ + 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 [yyyy] [name of copyright owner] + + 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. diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/README.md b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a38b01aa6c616ac68211060b794f91d71b088881 --- /dev/null +++ b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/README.md @@ -0,0 +1,109 @@ +## Pix2pose_ID1164_for_TensorFlow_ACL + +### 基本信息 + +**应用领域（Application Domain）：**6D Posture Estimation + +**修改时间（Modified） ：2022.4.17** + +**描述（Description）：基于TensorFlow框架的Pix2pose的6D姿态估计网络离线推理代码** + +### 概述 + +Pix2Pose是一种经典的6D姿势估计方法。该模型可以在没有纹理的3D模型的情况下预测每个目标像素的三维坐标，解决了遮挡、对称和无纹理等问题，仅使用RGB图像来估计物体的6D姿势，并且能够构建具有精确纹理的三维模型。Pix2Pose设计了一个自动编码器结构来估计三维坐标和每个像素的预期误差，然后在多个阶段使用这些像素的预测来形成二维到三维的对应关系，用RANSAC迭代的PnP算法直接计算姿态，并利用生成式对抗训练来精确地覆盖被遮挡的部分，对遮挡的情况具有鲁棒性，Pix2Pose还提出了一个新的损失函数，即变换器损失函数，用于将预测的姿态引导到最近的对称姿态来处理对称目标。 + +- 参考论文： + + [Park K , Patten T et al. "Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation." *2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2020.] +(https://arxiv.org/pdf/1908.07433.pdf) + +- 参考实现： + + [Pix2Pose](https://github.com/kirumang/Pix2Pose) + + + +### hdf5转pb + +本模型基于keras框架实现，训练模型时以HDF5格式保存模型训练的权重，使用hdf52pb.py将模型和权重转化为pb，我们提供转换好的[hdf5模型文件](obs://pix2pose/tless_inference/pix2pose_weights/)。 + +hdf52pb.py主要代码如下： +``` +def h5_to_pb(h5_weight_path, output_dir, out_prefix="output_", log_tensorboard=True): + if not os.path.exists(output_dir): + os.mkdir(output_dir) + + h5_model = build_model() + h5_model.load_weights(h5_weight_path) + + out_nodes = [] + for i in range(len(h5_model.outputs)): + out_nodes.append(out_prefix + str(i + 1)) + tf.identity(h5_model.output[i], out_prefix + str(i + 1)) + + model_name = os.path.splitext(os.path.split(h5_weight_path)[-1])[0] + index + '.pb' + + sess = K.get_session() + init_graph = sess.graph.as_graph_def() + main_graph = graph_util.convert_variables_to_constants(sess, init_graph, out_nodes) + graph_io.write_graph(main_graph, output_dir, name=model_name, as_text=False) + if log_tensorboard: + from tensorflow.python.tools import import_pb_to_tensorboard + import_pb_to_tensorboard.import_to_tensorboard(os.path.join(output_dir, model_name), output_dir) + +def build_model(): + h5_model = load_model(inference_model_hdf5) + return h5_model + +if __name__ == '__main__': + output_dir = os.path.join(output_path) + h5_weight_path=os.path.join(inference_weight_hdf5) + h5_to_pb(h5_weight_path, output_dir) + print('finished') +``` +我们提供转换好的[pb模型文件](obs://pix2pose/tless_inference/pb/)。 + +### pb转om +使用ATC模型转换工具进行模型转换时可以参考如下指令: +``` +atc --model=/home/HwHiAiUser/AscendProjects/path_to_file/file.pb --framework=3 --output=/home/HwHiAiUser/AscendProjects/path_to_file/filename_OM --soc_version=Ascend310 --input_shape="input_1:1,128,128,3" --log=info --out_nodes="output_1:0;output_2:0" +``` + +我们提供转换好的[om模型文件](obs://pix2pose/tless_inference/OM/)。 + +![输出结果](picture/pb2om.png) + +### msame工具 +我们采用msame工具进行离线推理，参考[msame简介](https://gitee.com/ascend/tools/tree/master/msame), 获取msame推理工具及使用方法。 + +获取到msame可执行文件之后，进行推理测试。 + +### 数据集转bin +该过程原训练代码3_train_pix2pose.py中generator_train.predict（）函数后加入以下代码，直接获取预处理好的图片，并以bin格式存储： +``` + if not (os.path.exists(weight_dir + "/pb_input/")): + os.makedirs(weight_dir + "/pb_input/") + + for i in range(n): + img_org = X_src[i] + inference = weight_dir + "/pb_input/" + str(i) + ".bin" + img_org.tofile(inference) +``` + +为了测试，我们提供了测试数据集,这是我们转换好的[bin文件](obs://pix2pose/tless_inference/bin_input/)。 + +### 推理测试 +使用msame推理工具，参考如下命令，发起推理测试： +``` +./msame --model "/home/HwHiAiUser/AscendProjects/path_to_file/filename_OM.om" --input "/home/HwHiAiUser/AscendProjects/path_to_file/bin_name.bin" --output "/home/HwHiAiUser/AscendProjects/Pix2pose/out " --outfmt TXT --loop 1 +``` +![输出结果](picture/om_output.png) + + + +最后，可视化后可以得到类似如下结果： +![可视化结果](picture/output_viz.png) + + + + diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/hdf52pb.py b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/hdf52pb.py new file mode 100644 index 0000000000000000000000000000000000000000..e36e59d1cfaafc40596859712b8c70495715b1a9 --- /dev/null +++ b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/hdf52pb.py @@ -0,0 +1,77 @@ +# Copyright 2017 The TensorFlow 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. +# ============================================================================ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# 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. +# =========================== +# Author : Ma Shiyuan +# Time : 2022/4 +# Language : Python +# =========================== +import os,sys +os.system("pip install keras==2.2.4") +print("-----------------------------------------") + +from keras.models import load_model +import tensorflow as tf +from keras import backend as K +from tensorflow.python.framework import graph_util, graph_io + +def h5_to_pb(h5_weight_path, output_dir, out_prefix="output_", log_tensorboard=True): + if not os.path.exists(output_dir): + os.mkdir(output_dir) + + h5_model = build_model() + h5_model.load_weights(h5_weight_path) + + out_nodes = [] + for i in range(len(h5_model.outputs)): + out_nodes.append(out_prefix + str(i + 1)) + tf.identity(h5_model.output[i], out_prefix + str(i + 1)) + + model_name = os.path.splitext(os.path.split(h5_weight_path)[-1])[0] + index + '.pb' + + sess = K.get_session() + init_graph = sess.graph.as_graph_def() + main_graph = graph_util.convert_variables_to_constants(sess, init_graph, out_nodes) + graph_io.write_graph(main_graph, output_dir, name=model_name, as_text=False) + if log_tensorboard: + from tensorflow.python.tools import import_pb_to_tensorboard + import_pb_to_tensorboard.import_to_tensorboard(os.path.join(output_dir, model_name), output_dir) + + +def build_model(): + inference_model_hdf5='' + h5_model = load_model(inference_model_hdf5) + return h5_model + + +if __name__ == '__main__': + output_path='' + inference_weight_hdf5='' + output_dir = os.path.join(output_path) + h5_weight_path=os.path.join(inference_weight_hdf5) + h5_to_pb(h5_weight_path, output_dir) + print('finished') \ No newline at end of file diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/modelzoo_level.txt b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/modelzoo_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..4f4eeb699cb9bfd53ef6361efe5807c90ff799c8 --- /dev/null +++ b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/modelzoo_level.txt @@ -0,0 +1,6 @@ +ModelConvert:OK +QuantStatus:NOK +FuncStatus:OK +PrecisionStatus:OK +AutoTune:NOK +PerfStatus:NOK diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/om_output.png b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/om_output.png new file mode 100644 index 0000000000000000000000000000000000000000..a9f9785d98b344ed545d6990d02c44c41423cf75 Binary files /dev/null and b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/om_output.png differ diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/output_viz.png b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/output_viz.png new file mode 100644 index 0000000000000000000000000000000000000000..0e7cf5acc5cf0e2b49d3490ffd11153f79baaa48 Binary files /dev/null and b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/output_viz.png differ diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/pb2om.png b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/pb2om.png new file mode 100644 index 0000000000000000000000000000000000000000..dafc79aa354030f56c78496a9a53a87b7c04970e Binary files /dev/null and b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/picture/pb2om.png differ diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/requirements.txt b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..ad87d4400008c9821a834ea4b30b0683c0f253ab --- /dev/null +++ b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/requirements.txt @@ -0,0 +1,6 @@ +python==3.7.5 +numpy==1.16.4 +tensorflow-gpu==1.15 +tensorboard==1.14.0 +matplotlib==2.2.3 +keras==2.2.4 diff --git a/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/txt2png.py b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/txt2png.py new file mode 100644 index 0000000000000000000000000000000000000000..79303da2505336f0ed87407e84cd3e57cc812158 --- /dev/null +++ b/ACL_TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow_ACL/txt2png.py @@ -0,0 +1,61 @@ +# Copyright 2017 The TensorFlow 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. +# ============================================================================ +# Copyright 2021 Huawei Technologies Co., Ltd +# +# 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 numpy as np +from PIL import Image +import argparse +import os +from glob import glob +import matplotlib.pyplot as plt + + +def main(): + parser = argparse.ArgumentParser(description='') + parser.add_argument('--atc_dir', dest='atc_dir', default='', help='directory for atc result') + parser.add_argument('--width', dest='width', type=int, default=128) + parser.add_argument('--height', dest='height', type=int, default=128) + + args = parser.parse_args() + + result = np.loadtxt(args.atc_dir, dtype=np.float) + print(result.shape) + result_1 = result.reshape(args.width, args.height, 3) + print(result_1) + # import pdb + # pdb.set_trace() + # im = Image.fromarray(np.clip(result_1 * 255.0, , 255.0).astype('uint8')) + # im = Image.fromarray(np.uint8((result_1+1)/2 *255)) + # image=np.uint8((result_1 + 1) / 2 * 255) + image = result_1 + plt.figure() + plt.imshow(image) + plt.show() + + + +if __name__ == '__main__': + main() \ No newline at end of file