opencv

Commit Graph

Author	SHA1	Message	Date
CNOCycle	7713c84465	Merge pull request #25297 from CNOCycle:tflite/transpose Support Transpose op in TFlite #25297 Merge with extra: https://github.com/opencv/opencv_extra/pull/1168 The purpose of this PR is to introduce support for the Transpose op in TFlite format and to add a shape comparison between the output tensors and the references. In some occasional cases, the shape of the output tensor is `[1,4,1,1]`, while the shape of the reference tensor is `[1,4]`. Consequently, the norm check incorrectly reports that the test has passed, as the residual is zero. Below is a Python script for generating testing data. The generated data can be integrated into the repo `opencv_extra`. ```python import numpy as np import tensorflow as tf PREFIX_TFL = '/path/to/opencv_extra/testdata/dnn/tflite/' def generator(input_tensor, model, saved_name): # convert keras model to .tflite format converter = tf.lite.TFLiteConverter.from_keras_model(model) #converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.optimizations = [None] tflite_model = converter.convert() with open(f'{PREFIX_TFL}/{saved_name}.tflite', 'wb') as f: f.write(tflite_model) # save the input tensor to .npy if input_tensor.ndim == 4: opencv_tensor = np.transpose(input_tensor, (0,3,1,2)) else: opencv_tensor = input_tensor opencv_tensor = np.copy(opencv_tensor, order='C').astype(np.float32) np.save(f'{PREFIX_TFL}/{saved_name}_inp.npy', opencv_tensor) # generate output tenosr and save it to .npy mat_out = model(input_tensor).numpy() mat_out = np.copy(mat_out, order='C').astype(np.float32) if mat_out.ndim == 4: mat_out = np.transpose(mat_out, (0,3,1,2)) interpreter = tf.lite.Interpreter(model_content=tflite_model) out_name = interpreter.get_output_details()[0]['name'] np.save(f'{PREFIX_TFL}/{saved_name}_out_{out_name}.npy', mat_out) def build_transpose(): model_name = "keras_permute" mat_in = np.array([[[1,2,3], [4,5,6]]], dtype=np.float32) model = tf.keras.Sequential() model.add(tf.keras.Input(shape=(2,3))) model.add(tf.keras.layers.Permute((2,1))) model.summary() generator(mat_in, model, model_name) if __name__ == '__main__': build_transpose() ``` ### Pull Request Readiness Checklist - [x] I agree to contribute to the project under Apache 2 License. - [X] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [X] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [X] The feature is well documented and sample code can be built with the project CMake	7 months ago
ecchen	e63690a2d9	Add a shape checker for tflite models	8 months ago
Dmitry Kurtaev	13c95efa74	Merge pull request #25312 from dkurt:dnn_hotfix_tflite Ownership check in TFLite importer #25312 ### Pull Request Readiness Checklist resolves https://github.com/opencv/opencv/issues/25310 See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	8 months ago
Dmitry Kurtaev	01dc010436	Merge pull request #25273 from dkurt:tflite_new_layers TFLite new layers #25273 ### Pull Request Readiness Checklist resolves https://github.com/opencv/opencv/issues/25272, https://github.com/opencv/opencv/issues/24965 Merge with extra: https://github.com/opencv/opencv_extra/pull/1160 See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	9 months ago
Dmitry Kurtaev	c7ec0d599a	Merge pull request #23987 from dkurt:openvino_int8_backend OpenVINO backend for INT8 models #23987 ### Pull Request Readiness Checklist TODO: - [x] DetectionOutput layer (https://github.com/opencv/opencv/pull/24069) - [x] Less FP32 fallbacks (i.e. Sigmoid, eltwise sum) - [x] Accuracy, performance tests (https://github.com/opencv/opencv/pull/24039) - [x] Single layer tests (convolution) - [x] ~~Fixes for OpenVINO 2022.1 (https://pullrequest.opencv.org/buildbot/builders/precommit_custom_linux/builds/100334)~~ Performace results for object detection model `coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite`: \| backend \| performance (median time) \| \|---\|---\| \| OpenCV \| 77.42ms \| \| OpenVINO 2023.0 \| 10.90ms \| CPU: `11th Gen Intel(R) Core(TM) i5-1135G7 @ 2.40GHz` Serialized model per-layer stats (note that Convolution should use `*_I8` primitives if they are quantized correctly): https://gist.github.com/dkurt/7772bbf1907035441bb5454f19f0feef --- See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	1 year ago
Dmitry Kurtaev	178fdbbda8	Merge pull request #24196 from dkurt:ov_backend_cleanups Use ngraph::Output in OpenVINO backend wrapper #24196 ### Pull Request Readiness Checklist resolves https://github.com/opencv/opencv/issues/24102 * Use `ngraph::Output<ngraph::Node>>` insead of `std::shared_ptr<ngraph::Node>` as a backend wrapper. It lets access to multi-output nodes: `588ddf1b18/modules/dnn/src/net_openvino.cpp (L501-L504)` * All layers can be customizable with OpenVINO >= 2022.1. nGraph reference code used for default layer implementation does not required CPU plugin also (might be tested by commenting CPU plugin at `/opt/intel/openvino/runtime/lib/intel64/plugins.xml`). * Correct inference if only intermediate blobs requested. See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	1 year ago
Dmitry Kurtaev	a0debc3a9a	Enable OpenVINO max pooling with indices since 2022.1	1 year ago
Dmitry Kurtaev	4b8aeb1129	Merge pull request #24039 from dkurt:tflite_test_backends TFLite models on different backends (tests and improvements) #24039 ### Pull Request Readiness Checklist * MaxUnpooling with OpenVINO * Fully connected with transposed inputs/weights with OpenVINO * Enable backends tests for TFLite (related to https://github.com/opencv/opencv/issues/23992#issuecomment-1640691722) * Increase existing tests thresholds See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	1 year ago
Dmitry Kurtaev	e41ba90f17	Merge pull request #24004 from dkurt:tflite_new_layers [TFLite] Pack layer and other fixes for SSD from Keras #24004 ### Pull Request Readiness Checklist resolves https://github.com/opencv/opencv/issues/23992 Merge with extra: https://github.com/opencv/opencv_extra/pull/1076 See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	1 year ago
Dmitry Kurtaev	aa57833ad5	Merge pull request #23409 from dkurt:dnn_tflite_quant Import and inference INT8 quantized TFLite model #23409 ### Pull Request Readiness Checklist * Support quantized TFLite models * Enable fused activations (FP32, INT8) Merge with extra: https://github.com/opencv/opencv_extra/pull/1048 ![res](https://user-images.githubusercontent.com/25801568/231433201-566b4bd6-ccff-462c-9e74-adbdcdf3648b.png) on the image, green boxes are from TFLite and red boxes from OpenCV See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	2 years ago
Dmitry Kurtaev	5df6b4a756	Merge pull request #23325 from dkurt:dnn_input_info Propagate inputs info for ONNX and TFLite models ### Pull Request Readiness Checklist Needed for generic applications such as benchmarking pipelines. So OpenCV can tell about the default input shapes specified in the models. See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	2 years ago
Alexander Alekhin	bdff0949bb	dnn(tflite): add 3rdparty flatbuffers with pre-generated schema	2 years ago
Dmitry Kurtaev	76350cd30f	Merge pull request #23161 from dkurt:dnn_tflite TFLite models importer * initial commit * Refactor TFLiteImporter * Better FlatBuffers detection * Add permute before 4D->3D reshape * Track layers layout * TFLite Convolution2DTransposeBias layer * Skip TFLite tests without FlatBuffers * Fix check of FlatBuffers in tests. Add readNetFromTFLite from buffer * TFLite Max Unpooling test * Add skip for TFLite unpooling test * Revert DW convolution workaround * Fix ObjC bindings * Better errors handling * Regenerate TFLite schema using flatc * dnn(tflite): more checks, better logging * Checks for unimplemented fusion. Fix tests	2 years ago

13 Commits (7e9ef4db86cd403a8817832c8e558ef82c17733b)