DeepDetect v0.21.0

Features

• add predict from video (02872eb)
• add video input connector and streaming endpoints (07644b4)
• allow pure negative samples for training object detectors with torch (cd23bad)
• bench: add monitoring of transform time (3f77d42)
• chain: add action to draw bboxes as trailing action (ae0a05f)
• chain: allow user to add their own custom actions (a470c7b)
• ml: added support for segformer with torch backend (ab03d1d)
• ml: random cropping for training segmentation models with torch (ac7ce0f)
• random crops for object detector training with torch backend (385122d)
• segmentation of large images with sliding window, example Python script (8528e9a)

Bug Fixes

• bbox clamping in torch inference (2d6efd3)
• caffe object detector training requires test set (2e4db7e)
• dataset output dimension after crop augmentation (636d455)
• detection/torch: correctly normalize MAP wrt torchlib outputs (b12d188)
• model.json file saving (809f00a)
• segmentation with torch backend + full cropping support (e14c3f2)
• torch MaP with bboxes (9bc840f)
• torch model published config file (b0d4e04)

Docker images:

• CPU version: docker pull jolibrain/deepdetect_cpu:v0.21.0
• GPU (CUDA only): docker pull jolibrain/deepdetect_gpu:v0.21.0
• GPU (CUDA and Tensorrt) :docker pull jolibrain/deepdetect_cpu_tensorrt:v0.21.0
• GPU with torch backend: docker pull jolibrain/deepdetect_gpu_torch:v0.21.0
• All images available on https://hub.docker.com/u/jolibrain