DeepDetect v0.17.0

Features

• ml: data augmentation for object detection with torch backend (95942b9)
• ml: Visformer architecture with torch backend (40ec03f)
• torch: add batch size > 1 for detection models (91bde66)
• torch: image data augmentation with random geometric perspectives (d163fd8)
• api: introduce predict output parameter (c9ee71a)
• api: use DTO for NCNN init parameters (2ee11f0)

Bug Fixes

• build: docker builds with tcmalloc (6b8411a)
• doc: api traced models list (342b909)
• graph: loading weights from previous model does not fail (5e7c8f6)
• torch: fix faster rcnn model export for training (cbbbd99)
• torch: retinanet now trains correctly (351d6c6)

Docker images:

• CPU version: docker pull jolibrain/deepdetect_cpu:v0.17.0
• GPU (CUDA only): docker pull jolibrain/deepdetect_gpu:v0.17.0
• GPU (CUDA and Tensorrt) :docker pull jolibrain/deepdetect_cpu_tensorrt:v0.17.0
• GPU with torch backend: docker pull jolibrain/deepdetect_gpu_torch:v0.17.0
• All images available on https://hub.docker.com/u/jolibrain