first commit

README.md

@@ -1,2 +1,27 @@
 # Yet-Another-Anime-Segmenter
-Instance segmentation for anime characters based on CondInst
+Instance segmentation for anime characters based on [CondInst](https://arxiv.org/abs/2003.05664), using the implementation from [AdelaiDet](https://github.com/aim-uofa/AdelaiDet) and [detectron2](https://github.com/facebookresearch/detectron2).
+
+Many thanks to [AniSeg](https://github.com/jerryli27/AniSeg) created by jerryli27, as part of the dataset originates from the segmentation data provided in this [repo](https://github.com/jerryli27/AniSeg#about-the-models). The rest of the dataset is retrieved from [Pixiv](https://www.pixiv.net/) and manually annotated.
+
+## Usage
+### Installation
+Both AdelaiDet and detectron2 are required. Please refer to the official guide from [AdelaiDet](https://github.com/aim-uofa/AdelaiDet#installation) and [detectron2](https://github.com/facebookresearch/detectron2/blob/master/INSTALL.md). A Colab tutorial is provided.
+
+### Inference
+1. Download the [pretrained model](https://drive.google.com/file/d/1-3S47uS4BSOdPmY0dKy99WA-DA7OUMq5/view?usp=sharing) and the config file.
+
+2. Run inference with
+   ```bash
+    python AdelaiDet/demo/demo.py \
+        --config-file path/to/config.yaml \
+        --input input1.jpg input2.jpg \
+        --opts MODEL.WEIGHTS path/to/pretrained/model
+   ```
+## Training and Results
+Training using transfer learning from a [pretrained model](https://github.com/aim-uofa/AdelaiDet#coco-instance-segmentation-baselines-with-condinst) on COCO Instance Segmentation. Parameters can be found in the config file.
+
+Dataset is augmented by placing segmentations on pure backgrounds.
+
+![sample1](./sample/64535234_p0_seg.jpg)
+![sample2](./sample/52206792_p0_seg.jpg)
+![sample3](./sample/64113607_p0_seg.jpg)