Agora board builds (Model Farm, verified on real boards)

NOTICE.md

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+# Provenance
+
+Resources are copied without binary changes from the APLUX Model Farm build `SAM2-tiny` that Agora verified on real boards (decoded sample check, then measured), pinned by sha256 in SHA256SUMS.
+
+Agora arranges files under targets/<SoC>/<precision>/ and adds model.json. AidLite, AidGen, AidVoice and the Qualcomm QNN runtime are separate dependencies with their own terms.

README.md

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+---
+license: other
+license_name: aplux-model-farm
+license_link: https://huggingface.co/APLUX-Agora/SAM2-tiny/blob/main/LICENSE_MODEL_FARM.pdf
+pipeline_tag: image-segmentation
+tags: [Agora, QNN, AIoT, Qualcomm]
+---
+
+# SAM2-tiny model resources
+
+SAM2-tiny 点提示图像分割，使用 NPU 图像编码器与原始 checkpoint 派生的 CPU 解码器。
+
+Board builds that [Agora](https://mega.aidlux.com) runs and measures on real Qualcomm boards. Try it online, without a board: https://mega.aidlux.com/models/sam2-tiny
+
+| SoC · board | Precisions | Measured on Agora (default precision) |
+| --- | --- | --- |
+| QCS8550 · 犀牛派 X1 (Rhino Pi X1) | FP16 | 300.2 ms |
+
+Task: 分割. Inputs: image (image). Outputs: masks (masks), out (json).
+
+## Download
+
+```bash
+export AGORA_WORKSPACE="$HOME/my-sam2-tiny"
+export AGORA_SOC='QCS8550'
+hf download APLUX-Agora/SAM2-tiny \
+  --include "targets/$AGORA_SOC/*" --local-dir "$AGORA_WORKSPACE/resources"
+```
+
+Each `targets/<SoC>/` holds `model.json` (default precision and variant paths) and one directory per precision. Context binaries are named `model.bin`; multi-file packages are kept as published by Model Farm.
+
+Pre- and post-processing, the runner and an exported project: open the model on Agora and choose “部署指南”, or export any workflow that uses it.
+
+## Licence and provenance
+
+Source model licence: see the original model's terms. 
+Converted, deployable resources: APLUX Model Farm License (LICENSE_MODEL_FARM.pdf). See NOTICE.md and SHA256SUMS.

SHA256SUMS

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+f8c55cd22e21940417d2f06684b67368f32aaa20b6049744290a03012da3d140  targets/QCS8550/FP16/composite.json
+64fec93130c31da0cd6f44beff7b060d82f698f13fdebf076a02ec1b916fdbe5  targets/QCS8550/FP16/decoder.onnx
+c0104afea8a72b6cc63ae9569e796783ce33fb4f13e71663730cc0e67ccabe58  targets/QCS8550/FP16/encoder.bin

targets/QCS8550/FP16/composite.json

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+{
+  "components": {
+    "decoder": "decoder.onnx",
+    "encoder": "encoder.bin"
+  },
+  "decoderRuntime": "onnx",
+  "kind": "prompt_sam",
+  "source": {
+    "decoder": {
+      "checkpointPath": "algorithm/pretrainWeights/sam2_hiera_tiny.pt",
+      "checkpointSha256": "65b50056e05bcb13694174f51bb6da89c894b57b75ccdf0ba6352c597c5d1125",
+      "derivedOnnxSha256": "64fec93130c31da0cd6f44beff7b060d82f698f13fdebf076a02ec1b916fdbe5",
+      "onnx": "1.20.0",
+      "opset": 17,
+      "projectId": 728,
+      "ref": "f143195df33e8fa84055e763106bf1d2a3e5c065",
+      "sourceFiles": {
+        "modeling/position_encoding.py": "f19556279ef68170fc64004f5a43d9600a603954b26e50665ee17627d3f9dbe8",
+        "modeling/sam/mask_decoder.py": "573eaa438a6de85bb186628ceb2425b6bcde0c2bc599bb56bb24d76a08dabf16",
+        "modeling/sam/prompt_encoder.py": "486596f5ba976cb9ced3836d65f1793dae586be2180567a451098f96c45ae401",
+        "modeling/sam/transformer.py": "747d4023a8f5566083304f70864605dbfd39382b35bed99fcdb6c0a55a7de38b",
+        "modeling/sam2_utils.py": "85f5b9474b382b2ee7e87f6f25db0590ba2b2fb7534bc4ace33f6ea9bc65c143",
+        "utils/misc.py": "2ca91323a2964622f54e6e928df1dccb1addc5851a4b7cb1783e0627ca49cbd2"
+      },
+      "torch": "2.9.1+cu126"
+    },
+    "encoder": {
+      "path": "models/QCS8550/FP16/sam2_encoder_qcs8550_fp16.qnn236.ctx.bin",
+      "projectId": 1325,
+      "ref": "ad32ab614421eac543959c756be789a6e6f338a2",
+      "sha256": "c0104afea8a72b6cc63ae9569e796783ce33fb4f13e71663730cc0e67ccabe58"
+    }
+  },
+  "version": 1
+}

targets/QCS8550/FP16/decoder.onnx

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+oid sha256:64fec93130c31da0cd6f44beff7b060d82f698f13fdebf076a02ec1b916fdbe5
+size 16376298

targets/QCS8550/FP16/encoder.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c0104afea8a72b6cc63ae9569e796783ce33fb4f13e71663730cc0e67ccabe58
+size 84330504

targets/QCS8550/model.json

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+{
+  "soc": "QCS8550",
+  "default_precision": "FP16",
+  "variants": {
+    "FP16": "FP16/"
+  }
+}