Update links after renaming the repo from segment-anything-2 to sam2 (#341)

This PR update repo links after we renamed the repo from `segment-anything-2` to `sam2`. It also changes `NAME` in setup.py to `SAM-2` (which is already the named used in pip setup since python packages don't allow whitespace)
This commit is contained in:
Ronghang Hu
2024-09-30 20:27:44 -07:00
committed by GitHub
parent 05d9e57fb3
commit 98fcb164bf
9 changed files with 28 additions and 28 deletions

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@@ -26,9 +26,9 @@
SAM 2 needs to be installed first before use. The code requires `python>=3.10`, as well as `torch>=2.3.1` and `torchvision>=0.18.1`. Please follow the instructions [here](https://pytorch.org/get-started/locally/) to install both PyTorch and TorchVision dependencies. You can install SAM 2 on a GPU machine using:
```bash
git clone https://github.com/facebookresearch/segment-anything-2.git
git clone https://github.com/facebookresearch/sam2.git
cd segment-anything-2 & pip install -e .
cd sam2 & pip install -e .
```
If you are installing on Windows, it's strongly recommended to use [Windows Subsystem for Linux (WSL)](https://learn.microsoft.com/en-us/windows/wsl/install) with Ubuntu.
@@ -86,9 +86,9 @@ with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
masks, _, _ = predictor.predict(<input_prompts>)
```
Please refer to the examples in [image_predictor_example.ipynb](./notebooks/image_predictor_example.ipynb) (also in Colab [here](https://colab.research.google.com/github/facebookresearch/segment-anything-2/blob/main/notebooks/image_predictor_example.ipynb)) for static image use cases.
Please refer to the examples in [image_predictor_example.ipynb](./notebooks/image_predictor_example.ipynb) (also in Colab [here](https://colab.research.google.com/github/facebookresearch/sam2/blob/main/notebooks/image_predictor_example.ipynb)) for static image use cases.
SAM 2 also supports automatic mask generation on images just like SAM. Please see [automatic_mask_generator_example.ipynb](./notebooks/automatic_mask_generator_example.ipynb) (also in Colab [here](https://colab.research.google.com/github/facebookresearch/segment-anything-2/blob/main/notebooks/automatic_mask_generator_example.ipynb)) for automatic mask generation in images.
SAM 2 also supports automatic mask generation on images just like SAM. Please see [automatic_mask_generator_example.ipynb](./notebooks/automatic_mask_generator_example.ipynb) (also in Colab [here](https://colab.research.google.com/github/facebookresearch/sam2/blob/main/notebooks/automatic_mask_generator_example.ipynb)) for automatic mask generation in images.
### Video prediction
@@ -113,7 +113,7 @@ with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
...
```
Please refer to the examples in [video_predictor_example.ipynb](./notebooks/video_predictor_example.ipynb) (also in Colab [here](https://colab.research.google.com/github/facebookresearch/segment-anything-2/blob/main/notebooks/video_predictor_example.ipynb)) for details on how to add click or box prompts, make refinements, and track multiple objects in videos.
Please refer to the examples in [video_predictor_example.ipynb](./notebooks/video_predictor_example.ipynb) (also in Colab [here](https://colab.research.google.com/github/facebookresearch/sam2/blob/main/notebooks/video_predictor_example.ipynb)) for details on how to add click or box prompts, make refinements, and track multiple objects in videos.
## Load from 🤗 Hugging Face