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Updated 2022 (markdown)
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## 2022-07-13
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## 2022-07-13
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* Vadim:
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* keep working on inference engine in Ficus. Several image classification models from ONNX model zoo are now supported: Squeeznet, EfficientNetv4-lite, Shufflenet, Googlenet, Inception v1 (v2 proces incorrect results, probably incorrect preprocessing; v3 fails to load because of using ONNX sequences). Now working on FP16 mode
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* GSoC: the 1st RISC-V PR is merged, now the student is preparing update to fix compile errors when all SIMD is turned off
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* OpenCV China: good progress on multi-task model (object detection + pose estimation + semantical segmentation), the quality is 2% lower than claimed in the paper, but the results look reasonably good.
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* OpenCV China: 2 PRs on text detection & recognition have been submitted (they contain benchmarks to evaluate quality).
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* OpenCV China: 1st PR on initial Ascend support (toolchain detection for now) is submitted.
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* FP16 acceleration of convolution is submitted, but fails to compile.
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* AR: invite mentors for the next Wednesday (GSoC phase 1 evaluation: July 25th - July 29th).
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* Alexander S (x.ai):
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* Done:
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* Aruco patch is ready and waiting for review (for ~2 weeks already).
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* Significant progress on CI. Even Android on 3.4 branch will likely be tested (using some old NDK release version). Megapack for Windows is not ready not.
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* 2 patches by Rostislav (ICP improvements) are ready for review.
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* Andrey:
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* Split PR docs workflows by a branch and updated docker images, 3.4 and 4.x based on Ubuntu 20.04, 5.x based on Ubuntu 22.04. [#35](https://github.com/opencv/ci-gha-workflow/pull/35), [#8](https://github.com/opencv-infrastructure/opencv-gha-dockerfile/pull/8)
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* Finished fixing compiling warnings in case of hosts issues on Linux x86_64 / ARM64 and macOS x86_64 / ARM64.
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* Fixed defining a path for a local variable to new DNN models on macOS. [#37](https://github.com/opencv/ci-gha-workflow/pull/37)
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* Created an issue about Java Finalize Class.[ #22260](https://github.com/opencv/opencv/issues/22260)
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* Renamed Ubuntu version from 1804 to 2004 for Linux ARM64 builds (just UI change). [#22266] (https://github.com/opencv/opencv/pull/22266), [#22267](https://github.com/opencv/opencv/pull/22267), [#22268](https://github.com/opencv/opencv/pull/22268)
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* Fixed an issue with the recursion in opencv-python using “ipython”. [#22269](https://github.com/opencv/opencv/pull/22269)
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* Alexander:
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* Migrated Android environment for 3.4 to old NDK 10e. Modern NDK is not filly supported there.
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* Reviewed, tested, helped to resolve issues with ## 22274, 22226, 22269, 22257, #22150, contrib #3240
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* In progress:
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* Andrey:
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* Fixing compiling warnings in case of hosts issues on Windows.
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* Rostislav:
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* Normal computer tests: draft PR #22241 filed; need to check all available data types & rewrite tests on Gtest params; add parameters to Linemod & expose CV_16U as available depth type
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* 3D module review [draft](https://docs.google.com/document/u/1/d/1cJQzE5c_4N6bltw0wR1KvEAeYa9U2-wqRAyjIXikn8M/edit) written, need to add notes on API consistency & Python wrappers available
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* Vincent:
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* porting internal calibration tool to OpenCV 4.x, submitted some PR with fixes
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* it would be nice to have an up-to-date comprehensive list of bit-exact functions somewhere
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* Shiqi Yu:
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* no updates so far.
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<pre>
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<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>
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</pre>
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## 2022-07-13
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* Vadim:
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* Vadim:
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* Keep working on Ficus NN. MobileNet-SSD and TinyYolo v3 are now supported. The further plans include 8-bit & Winograd convolution, FasterRCNN and Mark-RCNN support (ultimately, the goal is to support every single model in ONNX model zoo and OpenCV model zoo), engine refactoring and x86-64 support.
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* Keep working on Ficus NN. MobileNet-SSD and TinyYolo v3 are now supported. The further plans include 8-bit & Winograd convolution, FasterRCNN and Mark-RCNN support (ultimately, the goal is to support every single model in ONNX model zoo and OpenCV model zoo), engine refactoring and x86-64 support.
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* There is good progress on Loops JIT engine.
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* There is good progress on Loops JIT engine.
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