Update README.md

README.md

@@ -1,3 +1,55 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+---
+license: apache-2.0
+pipeline_tag: mask-generation
+tags:
+- sam2
+---
+
+# SAM2-Hiera-tiny
+
+This repository contains tiny variant of SAM2 model. SAM2 is the state-of-the-art mask generation model released by Meta.
+
+## Usage
+
+You can use it like below. First install packaged version of SAM2.
+
+```bash
+pip install samv2 huggingface_hub
+```
+
+Each model requires different classes to infer. 
+
+```python
+
+from huggingface_hub import hf_hub_download
+from sam2.build_sam import build_sam2
+from sam2.sam2_image_predictor import SAM2ImagePredictor
+
+hf_hub_download(repo_id = "merve/sam2-hiera-tiny", filename="sam2_hiera_tiny.pt", local_dir = "./")
+
+ckpt = f"./sam2_hiera_tiny.pt"
+config = "sam2_hiera_t.yaml"
+
+sam2_model = build_sam2(config, ckpt, device="cuda", apply_postprocessing=False)
+predictor = SAM2ImagePredictor(sam2_model)
+
+# it accepts coco format
+box = [x1, y1, w, h]
+predictor.set_image(image)
+
+masks = predictor.predict(box=box,
+multimask_output=False)
+```
+
+## Resources
+
+The team behind SAM2 made example notebooks for all tasks.
+
+- See [image predictor example](https://github.com/facebookresearch/segment-anything-2/blob/main/notebooks/image_predictor_example.ipynb) for full example on prompting.
+
+- See [automatic mask generation example](https://github.com/facebookresearch/segment-anything-2/blob/main/notebooks/automatic_mask_generator_example.ipynb) for generating all masks.
+
+- See [video object segmentation example](https://github.com/facebookresearch/segment-anything-2/blob/main/notebooks/video_predictor_example.ipynb)