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Image histogram equalization by the image input connector #778
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This does a histogram equalization of colored image. Closes jolibrain#778
sileht
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Sep 7, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
sileht
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Sep 8, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
sileht
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Sep 8, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
sileht
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Sep 8, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
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Sep 10, 2020
This does a histogram equalization of bw & colored image. Closes #778
sileht
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Sep 10, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
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Sep 14, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
sileht
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Sep 14, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
sileht
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Sep 17, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
sileht
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Sep 17, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
sileht
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Sep 17, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
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Sep 18, 2020
This does a histogram equalization of bw & colored image. Closes jolibrain#778
sileht
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Sep 18, 2020
This does a histogram equalization of bw & colored image. Closes #778
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# [0.10.0](v0.9.7...v0.10.0) (2020-10-05) ### Bug Fixes * missing variant package in docker files ([dcf738b](dcf738b)) * **build:** CUDA_ARCH not escaped correctly ([696087f](696087f)) * in tensorrt builds, remove forced cuda version and unused lib output + force-select tensorrt when tensorrt_oss is selected ([9430fb4](9430fb4)) * **clang-format:** signed/unsigned comparaison ([af8e144](af8e144)) * **clang-format:** signed/unsigned comparaison ([0ccabb6](0ccabb6)) * **dede:** Remove unnecessary caffe include that prevent build with torch only ([a471b82](a471b82)) * **docker:** install rapidjson-dev package ([30fb2ca](30fb2ca)) * **native:** do not raise exception if no template_param is given ([d0705ab](d0705ab)) * **nbeats:** correctly setup trend and seasonality models (implement paper version and not code version) ([75accc6](75accc6)) * **nbeats:** much lower memory use in case of large dim signals ([639e222](639e222)) * **tests:** inc iteration of torchapi.service_train_image test ([4c93ace](4c93ace)) * /api/ alias when deployed on deepdetect.com ([4736893](4736893)) * add support and automated processing of categorical variables in timeseries data ([1a9af3e](1a9af3e)) * allow serialization/deserializationt of Inf/-Inf/NaN ([976c892](976c892)) * allows to specify size and color/bw with segmentation models ([58ecb4a](58ecb4a)) * build with -DUSE_TENSORRT_OSS=ON ([39bd675](39bd675)) * convolution layer initialization of SE-ResNeXt network templates ([69ff0fb](69ff0fb)) * input image transforms in API doc ([f513f17](f513f17)) * install cmake version 3.10 ([10666b8](10666b8)) * race condition in xgboost|dede build ([fd32eae](fd32eae)) * replace db":true by db":false in json files when copying models ([06ac6df](06ac6df)) * set caffe smooth l1 loss threshold to 1 ([0e329f0](0e329f0)) * ssd_300_res_128 deploy file is missing a quote ([4e52a0e](4e52a0e)) * svm prediction with alll db combinations ([d8e2961](d8e2961)) * svm with db training ([6e925f2](6e925f2)) * tensorrt does not support blank_label ([7916500](7916500)) * update caffe cudnn engine without template ([ca58c51](ca58c51)) * **build:** ensure all xgboost submodules are checkouted ([12aaa1a](12aaa1a)) * **ci:** add CUDA_ARCH ([5b9eb15](5b9eb15)) * **ci:** add Jenkingfile symlink for old PR ([61e1176](61e1176)) * **ci:** add missing LD_LIBRARY_PATH for protoc ([cae5b1b](cae5b1b)) * **ci:** add missing steps block ([549bc59](549bc59)) * **ci:** cleanup workspace after artefact upload ([c9321cd](c9321cd)) * **ci:** fix dataset path location ([d071ff3](d071ff3)) * **ci:** fix deepdetect-pytorch project name ([0857b48](0857b48)) * **ci:** remove empty stage ([a7f56e4](a7f56e4)) * **ci:** run clang-format from build directory ([c51a022](c51a022)) * **ci:** typo in Jenkinfile ([a512f5b](a512f5b)) * **ci:** use correct cmake TORCH option ([1553327](1553327)) * **ci:** use unsuccessful instead of failure ([5dc1571](5dc1571)) * **clang-format:** typo in dataset tarball command ([04ddad7](04ddad7)) * **dede:** support all version of spdlog while building with syslog ([81f47c9](81f47c9)) * **torch:** handle case where sequence data is < wanted timestep ([b6d394a](b6d394a)) * **TRT:** refinedet ([b6152b6](b6152b6)) * unusual builds (ie w/o torch or with tsne only lead to build errors ([241bf6b](241bf6b)) ### Features * **build:** add script to create cppnet-lib debian package ([28247b4](28247b4)) * **build:** allow to change CUDA_ARCH ([67ad43e](67ad43e)) * **ci:** add cache for examples/ dataset ([4c19d78](4c19d78)) * **ci:** add new jenkins job to cache pytorch build ([43c9c06](43c9c06)) * **ci:** enable ccache ([c72327d](c72327d)) * **ci:** lock the GPU for running tests ([dd28248](dd28248)) * **ci:** only build last version of a branch ([53edf52](53edf52)) * **ci:** use prebuilt dataset for unittests ([28ab168](28ab168)) * **dede:** Training for image classification with torch ([6e81915](6e81915)) * **graph:** lstm autoencoder ([038a74c](038a74c)) * **imginputfile:** histogram equalization of input image ([2f0061c](2f0061c)), closes [#778](#778) * **stats:** added service statistics mechanism ([1839e4a](1839e4a)) * **torch:** in case of timeseries, warn if file do not contain enough timesteps ([1a5f905](1a5f905)) * **torch:** nbeats ([f288665](f288665)) * **torch:** upgrade to torch 1.6 ([f8f7dbb](f8f7dbb)) * **torch,native:** extract_layer ([d37e182](d37e182)) * add json output to dd_bench.py ([874fc01](874fc01)) * added bw image input support to dd_bench ([6e558d6](6e558d6)) * **trains-status:** add tflops to body.measures ([af31c8b](af31c8b)), closes [#785](#785) * Docker images optimization ([fba637a](fba637a)) * format the code with clang-format ([07d6bdc](07d6bdc)) * LSTM over torch , preliminary internal graph representation ([25faa8b](25faa8b)) * update all docker images to ubuntu 18.04 ([eaf0421](eaf0421))
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Having OpenCV's histogram equalization directly executed by the input connector is useful in some cases for both training and inference.
We suggest a
eqhist
boolean parameter to be added to theinput
JSON object on both training and predict calls.I guess this could go after the
rgb
check here: https://github.com/jolibrain/deepdetect/blob/master/src/imginputfileconn.h#L104The function to apply from OpenCV should be:
Beware that equalization is per channel, so the call above may only work when the image is single channel B&W, which is our motivating use case actually. For RGB images, the equalization may need to be applied per channel.
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