DeepDetect v0.23.0

Features

• add crnn resnet native template (ec1f8ad)
• add deepdetect version to config variables for external projects (be79e54)
• dlib: update dlib backend (12d181f)
• torch: add multilabel classification (90d536e)
• torch: allow multigpu for traced models (6b3b9c0)
• torch: best model is computed over all the test sets (fbedf80)
• torch: update torch to 1.12 (7172314)
• yolox: export directly from trained dd repo to onnx (a612539)

Bug Fixes

• adamw default weight decay with torch backend (eb0cf83)
• add missing headers in predict_out.hpp (b23298f)
• docker: add libcupti to gpu_torch docker (1a5cd09)
• enable caffe chain with DTO & custom actions (d3e722e)
• exported yolox have the correct number of classes (4dac269)
• missing ifdef (e8a70cf)
• missing path to cub headers in tensorrt-oss build for jetson nano (00df9fd)
• oatpp: oatpp-zlib memory leak (fccd9a6)
• prevent a buggy optimization in traced fasterrcnn (dab88ca)
• reload best metric correctly after resume (c15c502)
• torch: OCR predict with native model (24aa37c)

Docker images:

• CPU version: docker pull jolibrain/deepdetect_cpu:v0.23.0
• GPU (CUDA only): docker pull jolibrain/deepdetect_gpu:v0.23.0
• GPU (CUDA and Tensorrt) :docker pull jolibrain/deepdetect_cpu_tensorrt:v0.23.0
• GPU with torch backend: docker pull jolibrain/deepdetect_gpu_torch:v0.23.0
• All images available on https://hub.docker.com/u/jolibrain