In this PR, we switch to a new implementation of the class `SAM2VideoPredictor` for in sam2/sam2_video_predictor.py, which allows for independent per-object inference.
Specifically, the new `SAM2VideoPredictor`:
* it handles the inference of each object separately, as if we are opening a separate session for each object
* it relaxes the assumption on prompting
* previously if a frame receives clicks only for a subset of objects, the rest of (non-prompted) objects are assumed to be non-existing in this frame
* now if a frame receives clicks only for a subset of objects, we don't make any assumptions for the remaining (non-prompted) objects
* it allows adding new objects after tracking starts
* (The previous implementation is backed up to `SAM2VideoPredictor` in sam2/sam2_video_predictor_legacy.py)
Also, fix a small typo `APP_URL` => `API_URL` in the doc.
Test plan: tested with the predictor notebook `notebooks/video_predictor_example.ipynb` and VOS script `tools/vos_inference.py`. Also tested with the demo.
Summary:
The Strawberry GraphQL library recently disabled multipart requests by default. This resulted in a video upload request returning "Unsupported content type" instead of uploading the video, processing it, and returning the video path.
This issue was raised in #361. A forward fix is to add `multipart_uploads_enabled=True` to the endpoint view.
Test Plan:
Tested locally with cURL and upload succeeds
*Request*
```
curl http://localhost:7263/graphql \
-F operations='{ "query": "mutation($file: Upload!){ uploadVideo(file: $file) { path } }", "variables": { "file": null } }' \
-F map='{ "file": ["variables.file"] }' \
-F file=@video.mov
```
*Response*
```
{"data": {"uploadVideo": {"path": "uploads/<HASH>.mp4"}}}
```
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)
