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Update copyright headers

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This commit is contained in:
Nikhila Ravi
2023-04-12 00:22:55 -07:00
parent d398eb176f
commit e72b94dbed
11 changed files with 71 additions and 5 deletions
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demo/README.md
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@@ -1,11 +1,19 @@
## Segment Anything Simple Web demo
This **front-end only** demo shows how to load a fixed image and `.npy` file of the SAM image embedding, and run the SAM ONNX model in the browser using Web Assembly with mulithreading enabled by `SharedArrayBuffer`, Web Worker, and SIMD128.
This **front-end only** React based web demo shows how to load a fixed image and corresponding `.npy` file of the SAM image embedding, and run the SAM ONNX model in the browser using Web Assembly with mulithreading enabled by `SharedArrayBuffer`, Web Worker, and SIMD128.
<img src="https://github.com/facebookresearch/segment-anything/raw/main/assets/minidemo.gif" width="500"/>
## Run the app
Install Yarn
```
npm install --g yarn
```
Build and run:
```
yarn && yarn start
```
@@ -18,7 +26,7 @@ Move your cursor around to see the mask prediction update in real time.
In the [ONNX Model Example notebook](https://github.com/facebookresearch/segment-anything/blob/main/notebooks/onnx_model_example.ipynb) upload the image of your choice and generate and save corresponding embedding.
Initialize the predictor
Initialize the predictor:
```python
checkpoint = "sam_vit_h_4b8939.pth"
@@ -28,7 +36,7 @@ sam.to(device='cuda')
predictor = SamPredictor(sam)
```
Set the new image and export the embedding
Set the new image and export the embedding:
```
image = cv2.imread('src/assets/dogs.jpg')
@@ -37,7 +45,7 @@ image_embedding = predictor.get_image_embedding().cpu().numpy()
np.save("dogs_embedding.npy", image_embedding)
```
Save the new image and embedding in `/assets/data`.
Save the new image and embedding in `src/assets/data`.
## Export the ONNX model