initial release

2026-07-05 18:11:23 +07:00
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+# SAM.cpp
+
+Inference of Meta's [Segment Anything Model](https://github.com/facebookresearch/segment-anything/) in pure C/C++
+
+## Description
+
+The example currently supports only the [ViT-B SAM model checkpoint](https://huggingface.co/facebook/sam-vit-base).
+
+## Next steps
+
+- [X] Reduce memory usage by utilizing the new ggml-alloc
+- [X] Remove redundant graph nodes
+- [ ] Make inference faster
+- [X] Fix the difference in output masks compared to the PyTorch implementation
+- [X] Filter masks based on stability score
+- [ ] Add support for user input
+- [ ] Support F16 for heavy F32 ops
+- [ ] Test quantization
+- [X] Support bigger model checkpoints
+- [ ] GPU support
+
+## Quick start
+Setup Python and build examples according to main README.
+
+```bash
+# Download PTH model
+wget -P examples/sam/ https://dl.fbaipublicfiles.com/segment_anything/sam_vit_b_01ec64.pth
+
+# Convert PTH model to ggml
+python examples/sam/convert-pth-to-ggml.py examples/sam/sam_vit_b_01ec64.pth examples/sam/ 1
+
+# run inference
+./bin/sam -t 16 -i ../examples/sam/example.jpg -m ../examples/sam/ggml-model-f16.bin
+```
+
+## Downloading and converting the model checkpoints
+
+You can download a [model checkpoint](https://github.com/facebookresearch/segment-anything/tree/main#model-checkpoints) and convert it to `ggml` format using the script `convert-pth-to-ggml.py`:
+
+## Example output on M2 Ultra
+```
+ $ ▶ make -j sam && time ./bin/sam -t 8 -i img.jpg
+[ 28%] Built target common
+[ 71%] Built target ggml
+[100%] Built target sam
+main: seed = 1693224265
+main: loaded image 'img.jpg' (680 x 453)
+sam_image_preprocess: scale = 0.664062
+main: preprocessed image (1024 x 1024)
+sam_model_load: loading model from 'models/sam-vit-b/ggml-model-f16.bin' - please wait ...
+sam_model_load: n_enc_state      = 768
+sam_model_load: n_enc_layer      = 12
+sam_model_load: n_enc_head       = 12
+sam_model_load: n_enc_out_chans  = 256
+sam_model_load: n_pt_embd        = 4
+sam_model_load: ftype            = 1
+sam_model_load: qntvr            = 0
+operator(): ggml ctx size = 202.32 MB
+sam_model_load: ...................................... done
+sam_model_load: model size =   185.05 MB / num tensors = 304
+embd_img
+dims: 64 64 256 1 f32
+First & Last 10 elements:
+-0.05117 -0.06408 -0.07154 -0.06991 -0.07212 -0.07690 -0.07508 -0.07281 -0.07383 -0.06779
+0.01589 0.01775 0.02250 0.01675 0.01766 0.01661 0.01811 0.02051 0.02103 0.03382
+sum:  12736.272313
+
+Skipping mask 0 with iou 0.705935 below threshold 0.880000
+Skipping mask 1 with iou 0.762136 below threshold 0.880000
+Mask 2: iou = 0.947081, stability_score = 0.955437, bbox (371, 436), (144, 168)
+
+
+main:     load time =    51.28 ms
+main:    total time =  2047.49 ms
+
+real	0m2.068s
+user	0m16.343s
+sys	0m0.214s
+```
+
+Input point is (414.375, 162.796875) (currently hardcoded)
+
+Input image:
+
+![llamas](https://user-images.githubusercontent.com/8558655/261301565-37b7bf4b-bf91-40cf-8ec1-1532316e1612.jpg)
+
+Output mask (mask_out_2.png in build folder):
+
+![mask_glasses](https://user-images.githubusercontent.com/8558655/263706800-47eeea30-1457-4c87-938b-8f11536c5aa7.png)
+
+## References
+
+- [ggml](https://github.com/ggerganov/ggml)
+- [SAM](https://segment-anything.com/)
+- [SAM demo](https://segment-anything.com/demo)