Upload YOLACT-ResNet50-OpenVINO: ONNX, OpenVINO IR, Intel NPU blob, card and manifest

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README.md

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+---
+license: mit
+base_model: litert-community/YOLACT-ResNet50-LiteRT
+base_model_relation: quantized
+library_name: openvino
+pipeline_tag: image-segmentation
+tags:
+- openvino
+- onnx
+- intel-npu
+---
+
+# YOLACT-ResNet50-OpenVINO
+
+YOLACT-ResNet50 for Intel NPUs, GPUs and CPUs: yolact from [litert-community/YOLACT-ResNet50-LiteRT](https://huggingface.co/litert-community/YOLACT-ResNet50-LiteRT/tree/3ecb14b9c4635cd87b515e1d12201c2c1631e19c) as ONNX (tf2onnx 1.17.0, opset 17), OpenVINO IR with fp32 weights, and a precompiled Intel NPU blob. On the NPU of a Core Ultra 9 386H the blob runs in 16.29 ms per run, numpy input to numpy output.
+
+Scripts, raw records, and the same table for all 52 graphs of LiteRT-Models: https://github.com/john-rocky/windows-zoo
+
+## Files
+
+| file | bytes | sha256 |
+|---|---|---|
+| `yolact.onnx` | 124,705,334 | `414d1e9ad7c8e9075e0f285ae794307beaa5befe785b5fda22f1e0cc7cfb6eed` |
+| `openvino/yolact.xml` | 789,193 | `4ff0eaf04fbf3f1f20531b03bf7bc799665aab73cc5872e14f1092e58206a6c3` |
+| `openvino/yolact.bin` | 124,471,816 | `7d0014086613dd81ec686a5280679415df07d08b202883e4cbfe708007db2751` |
+| `npu/yolact.blob` | 71,868,566 | `5a9dfa91a4a2a238c519439f48b795724890a4e15d5a0bb3e669958933f21961` |
+
+The NPU blob was compiled with OpenVINO 2026.4.1, Intel NPU driver 32.0.100.4841 (OpenVINO reports NPU_DRIVER_VERSION 1004841, NPU_COMPILER_VERSION 524292). If `import_model` refuses a blob on another driver or OpenVINO version, compile the IR instead (the commented line in the snippet).
+
+## How it was measured
+
+MSI Stealth 16 AI+ (Core Ultra 9 386H, RTX 5080 Laptop GPU at a 95 W power limit, Windows 11 build 26200.9711, on AC power), 2026-11-06. On the laptop, each row is one process: load, one run, 5 warmup runs, then the median of 30 timed runs (2 warmup + 10 timed runs when the first run takes more than 3 s), numpy input to numpy output, every runtime at its default settings, one process at a time, each started after the CPU, the RTX and the Intel GPU had gone idle (the thresholds are in METHOD.md of the GitHub repo). Output check: each output against the CPU output in fp32 on the same input (OpenVINO on the CPU, as ONNX Runtime 1.31.1 cannot load this file); PASS = cosine ≥ 0.99, no NaN or Inf, and top-1 agreement ≥ 0.99 for class scores.
+
+## Speed and output check
+
+| processor | runtime | file | ms | load s | output check |
+|---|---|---|---|---|---|
+| Intel AI Boost NPU | OpenVINO 2026.4.1 | `npu/` blob (`import_model`) | 16.29 | 0.04 | PASS (cos ≥ 0.9999) |
+| Intel AI Boost NPU | ONNX Runtime 1.31.1 + OpenVINO EP 1.8.1 | `.onnx`, compiled when the session loads | - | - | did not run |
+| Intel Graphics (iGPU) | ONNX Runtime 1.31.1 + OpenVINO EP 1.8.1 | `.onnx` | - | - | did not run |
+| RTX 5080 Laptop (95 W limit) | ONNX Runtime 1.31.1, CUDA EP | fp16 copy of the `.onnx` (not in this repo) | - | - | did not run |
+| RTX 5080 Laptop (95 W limit) | ONNX Runtime 1.31.1, CUDA EP | `.onnx` | - | - | did not run |
+| Core Ultra 9 386H CPU | ONNX Runtime 1.31.1, CPU EP | `.onnx` | - | - | did not run |
+| Core Ultra 9 386H CPU | OpenVINO 2026.4.1 | `.onnx`, f32 | - | - | reference (ONNX Runtime 1.31.1 cannot load this file) |
+
+The ONNX file against the source `.tflite` (LiteRT interpreter on the CPU, the same input): PASS, cosine ≥ 0.9999 for every output.
+
+## Run it on the Intel NPU
+
+Download this repo, then run the snippets from its folder:
+
+```sh
+pip install huggingface_hub
+hf download mlboydaisuke/YOLACT-ResNet50-OpenVINO --local-dir YOLACT-ResNet50-OpenVINO
+cd YOLACT-ResNet50-OpenVINO
+```
+
+OpenVINO (`pip install openvino==2026.4.1`):
+
+```python
+import numpy as np
+import openvino as ov
+
+core = ov.Core()
+if "NPU" not in core.available_devices:
+    raise SystemExit(f"no Intel NPU visible to OpenVINO: {core.available_devices}")
+with open("npu/yolact.blob", "rb") as f:
+    compiled = core.import_model(f.read(), "NPU")  # precompiled: no compile at load
+# or compile the IR on this machine: compiled = core.compile_model("openvino/yolact.xml", "NPU")
+# replace the zeros with your preprocessed input (float32, the shapes printed by compiled.inputs)
+feeds = {i.get_any_name(): np.zeros(list(i.shape), np.float32) for i in compiled.inputs}
+outputs = compiled(feeds)
+print({o.get_any_name(): outputs[o].shape for o in compiled.outputs})
+```
+
+ONNX Runtime 1.31.1 with the OpenVINO EP 1.8.1 does not run `yolact.onnx` on the NPU: the session fails to load (`onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Load model from C:\src\zoo\onnx\yolact.onnx failed:Node (__main__.Wrap/yolact.`). The OpenVINO lines above run it.
+
+## Licence
+
+MIT, the licence of [litert-community/YOLACT-ResNet50-LiteRT](https://huggingface.co/litert-community/YOLACT-ResNet50-LiteRT). The upstream model: [dbolya/yolact-resnet50](https://huggingface.co/dbolya/yolact-resnet50).

manifest.json

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+{
+ "source_repo": "litert-community/YOLACT-ResNet50-LiteRT",
+ "source_revision": "3ecb14b9c4635cd87b515e1d12201c2c1631e19c",
+ "graphs": {
+  "yolact": {
+   "from": "yolact",
+   "ir": {
+    "openvino": "2026.4.1-22982-e213a147257-releases/2026/4",
+    "compress_to_fp16": false
+   },
+   "blob_compiled_with": {
+    "openvino": "2026.4.1-22982-e213a147257-releases/2026/4",
+    "FULL_DEVICE_NAME": "Intel(R) AI Boost",
+    "NPU_DRIVER_VERSION": "1004841",
+    "NPU_COMPILER_VERSION": "524292",
+    "NPU_COMPILER_TYPE": "CompilerType.PREFER_PLUGIN",
+    "INFERENCE_PRECISION_HINT": "<Type: 'float16'>"
+   },
+   "files": {
+    "yolact.onnx": {
+     "bytes": 124705334,
+     "sha256": "414d1e9ad7c8e9075e0f285ae794307beaa5befe785b5fda22f1e0cc7cfb6eed"
+    },
+    "openvino/yolact.xml": {
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+     "sha256": "4ff0eaf04fbf3f1f20531b03bf7bc799665aab73cc5872e14f1092e58206a6c3"
+    },
+    "openvino/yolact.bin": {
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+     "sha256": "7d0014086613dd81ec686a5280679415df07d08b202883e4cbfe708007db2751"
+    },
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+     "sha256": "5a9dfa91a4a2a238c519439f48b795724890a4e15d5a0bb3e669958933f21961"
+    }
+   }
+  }
+ }
+}

npu/yolact.blob

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yolact.onnx

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