R-4.5.0

Open OPHoperHPO opened this issue 1 year ago • 1 comments

Changelog:

Removed obsolete models
Fixed typos in tracer b7
Added new AutoScene preprocessing method
Added warning about fp16 to u2net class
Updated README.
Changelog
Added ISNet segmentation network #119
Added object classifier YOLOv4.
Added AutoInterface to automatically select the best methods for images with different scene types. AutoInterface uses a scene classifier and an object classifier to perform full analysis on all images. At the moment, since there are not enough models for so many types of scenes, universal models are selected for some domains. In the future, when some variety of models is added, auto-selection will be rewritten for the better.
Updated metrics
Added CascadePSP segmentation refinement network. It will refine the segmentation mask before passing it to the matting network. This should provide more accurate background removal for objects and people. (Check repo from CREDITS.md for more details)
Fixed trimap generator unknown area value as FBA Matting expect.
Added noise filter switch (needed for smooth mask prediction on the final stage for soft scenes)
Updated alpha composition algorithm

AutoScene RC-4.2.0

Description

It performs a primary analysis of the image in order to automatically select the necessary method for removing the background. The choice is made by classifying the scene type.

Model accuracy:

Model achieves 91.3% accuracy on the validation set.

Classes info

The output can be the following types:

hard
soft
digital*

The hard class denotes a group of scenes to which a coarser background removal method should be applied, intended for objects with an edge without small details. The hard class contains the following categories of objects: object, laptop, charger, pc mouse, pc, rocks, table, bed, box, sneakers, ship, wire, guitar, fork, spoon, plate, keyboard, car, bus, screwdriver, ball, door, flower, clocks, fruit , food, robot.

The soft class denotes a group of scenes to which you want to apply a soft background removal method intended for people, hair, clothes, and other similar types of objects. The soft class contains the following categories of objects: animal, people, human, man, woman, t-shirt, hairs, hair, dog, cat, monkey, cow, medusa, clothes

The digital* class denotes a group of images with digital graphics, such as screenshots, logos, and so on. The digital class contains the following categories of scenes: screenshot