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DeepDetect v0.14.0
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@beniz beniz released this 05 Mar 10:16
· 359 commits to master since this release
v0.14.0
4de3807

Features

  • bench: Add parameters for torch image backend (5d24f3d)
  • ml: ViT support for Realformer from https://arxiv.org/abs/2012.11747v2 (5312de7)
  • nbeats: add parameter coefficient to backcast loss (35b3c31)
  • torch: add inference for torch detection models (516eeb6)
  • torch: Sharpness Aware Minimization (2010.01412) (45a8408)
  • torch: support for multiple test sets (c0dcec9)
  • torch: temporal transformers (encoder only) (non autoreg) (3538eb7)
  • CSV parser support for quotes and string labels (efa4c79)
  • new cropping action parameters in chains (6597b53)
  • running custom methods from jit models (73d1eef)
  • torch/txt: display msg if vocab not found (31837ec)
  • SSD MAP-x threshold control (acd252a)
  • use oatpp::DTO to parse img-input-connector APIData (33aee72)

Bug Fixes

  • build: pytorch with custom spdlog (1fb19a0)
  • caffe/cudnn: force default engine option in case of cudnn not compiled in (b6dec4e)
  • chore: typo when trying to use syslog (374e6c4)
  • client: Change python package name to dd_client (b96b0fa)
  • csvts: read from memory (6d1dba8)
  • csvts: throw proper error when a csv file is passed at training time (90aab20)
  • docker: ensure pip3 is working on all images (a374a58)
  • ncnn: update innerproduct so that it does not pack data (9d88187)
  • torch: add error message when repository contains multiple models (a08285f)
  • -Werror=deprecated-copy gcc 9.3 (0371cfa)
  • action cv macros with opencv >= 3 (37d2926)
  • caffe build spdlog dependency (62e781a)
  • docker /opt/models permissions (82e2695)
  • prevent softmax after layer extraction (cbee659)
  • tag syntax for github releases (4de3807)
  • torch backend CPU build and tests (44343f6)
  • typo in oatpp chain HTTP endpoint (955b178)
  • torch: gather torchscript model parameters correctly (99e4dbe)
  • torch: set seed of torchdataset during training (d02404a)
  • torch/ranger: allow not to use lookahead (d428d08)
  • torch/timeseries: in case of db, correctly finalize db (aabedbd)

Docker images:

  • CPU version: docker pull jolibrain/deepdetect_cpu:v0.14.0
  • GPU (CUDA only): docker pull jolibrain/deepdetect_gpu:v0.14.0
  • GPU (CUDA and Tensorrt) :docker pull jolibrain/deepdetect_cpu_tensorrt:v0.14.0
  • GPU with torch backend: docker pull jolibrain/deepdetect_gpu_torch:v0.14.0
  • All images available on https://hub.docker.com/u/jolibrain
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