FlowPilot-DST streaming ONNX (one frame per call, feature buffer) for small and dune; README
Browse files- README.md +40 -3
- flowpilot-dst-dune/flowpilot_dst_dune_vitb14_streaming.inputs.npz +3 -0
- flowpilot-dst-dune/flowpilot_dst_dune_vitb14_streaming.metadata.json +174 -0
- flowpilot-dst-dune/flowpilot_dst_dune_vitb14_streaming.onnx +3 -0
- flowpilot-dst-small/flowpilot_dst_fastvit_t12_streaming.inputs.npz +3 -0
- flowpilot-dst-small/flowpilot_dst_fastvit_t12_streaming.metadata.json +174 -0
- flowpilot-dst-small/flowpilot_dst_fastvit_t12_streaming.onnx +3 -0
README.md
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@@ -12,8 +12,9 @@ tags:
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# Visual Navigation Model Checkpoints
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Pretrained navigation policies trained with [VisNavKit](https://github.com/VAIL-UCLA/visnavkit).
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-
Each folder holds one model: the Lightning checkpoint, its ONNX
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(shapes, anchor times, SHA-256 of both files, PyTorch/ONNX parity) and a sample
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| Folder | VisNavKit config | Model | Params | Val top-1 ADE@1/2/4 s (m) | Val top-1 FDE (m) |
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| --- | --- | --- | --- | --- | --- |
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<folder>/flowpilot_dst_<encoder>.onnx # deployment graph
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<folder>/flowpilot_dst_<encoder>.metadata.json # shapes, anchor times, hashes, parity
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<folder>/flowpilot_dst_<encoder>.inputs.npz # traced sample inputs for a smoke run
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```
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## Usage
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speed/yaw rate and action bounds. The full contract, including frame preparation, is in
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[FlowPilot-DST ONNX IO](https://github.com/VAIL-UCLA/visnavkit/blob/dev/docs/flowpilot_dst_onnx.md).
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```bash
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uv run visnavkit-export-dst checkpoint=flowpilot_dst_fastvit_t12.ckpt output=flowpilot_dst_fastvit_t12.onnx
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# Visual Navigation Model Checkpoints
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Pretrained navigation policies trained with [VisNavKit](https://github.com/VAIL-UCLA/visnavkit).
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+
Each folder holds one model: the Lightning checkpoint, its two ONNX exports (window and streaming),
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the export metadata (shapes, anchor times, SHA-256 of both files, PyTorch/ONNX parity) and a sample
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input batch.
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| Folder | VisNavKit config | Model | Params | Val top-1 ADE@1/2/4 s (m) | Val top-1 FDE (m) |
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| --- | --- | --- | --- | --- | --- |
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<folder>/flowpilot_dst_<encoder>.onnx # deployment graph
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<folder>/flowpilot_dst_<encoder>.metadata.json # shapes, anchor times, hashes, parity
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<folder>/flowpilot_dst_<encoder>.inputs.npz # traced sample inputs for a smoke run
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<folder>/flowpilot_dst_<encoder>_streaming.{onnx,metadata.json,inputs.npz} # streaming graph, same weights
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```
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## Usage
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speed/yaw rate and action bounds. The full contract, including frame preparation, is in
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[FlowPilot-DST ONNX IO](https://github.com/VAIL-UCLA/visnavkit/blob/dev/docs/flowpilot_dst_onnx.md).
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### Streaming ONNX
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`*_streaming.onnx` runs one frame per call. It caches each past frame's features (`[global image
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feature | route latent]`) in a buffer, encodes only the current frame, and decodes only the current
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plan. After 20 frames its decision equals the window graph's (checked at export: DST exact, DUNE
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to 5e-7 in ONNX Runtime).
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| input | shape | meaning |
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| --- | --- | --- |
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| `vision` | small (1, 2, 3, 216, 384): [previous, current]; dune (1, 1, 3, 216, 384) | the current frame; for small, the previous frame is all zeros on the first call |
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| `route_patch`, `goal`, `ego` | (1, 1, 80, 80), (1, 1, 3), (1, 1, 2) | the current frame's route, goal, `[v, w]` |
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| `action_bounds` | (1, 2, 5) | as in the window graph |
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| `feat_buffer` | (1, 19, F): F = 768 small, 2048 dune | the last call's `feat_buffer_out`; zeros at startup |
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| `buffer_mask` | (1, 19) | the last call's `buffer_mask_out`; zeros at startup |
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Outputs: `modes`, `probs`, `speed` as in the window graph, plus `feat_buffer_out`, `buffer_mask_out`.
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```python
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stem = "flowpilot-dst-dune/flowpilot_dst_dune_vitb14_streaming"
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session = ort.InferenceSession(hf_hub_download(repo, f"{stem}.onnx"))
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buf, mask = np.zeros((1, 19, 2048), np.float32), np.zeros((1, 19), np.float32)
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for frame, route, goal, ego in stream: # 20 Hz, frames exactly 50 ms apart
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modes, probs, speed, buf, mask = session.run(None, dict(
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vision=frame[None, None], route_patch=route[None, None], goal=goal[None, None],
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ego=ego[None, None], action_bounds=bounds, feat_buffer=buf, buffer_mask=mask))
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plan = modes[0, 0] # (80, 5)
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```
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- Feed `feat_buffer_out` and `buffer_mask_out` back unchanged.
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- Call once per frame at 20 Hz. Don't skip frames. Reset the buffer (and, for small, the previous
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frame) to zeros after a gap or restart.
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- Keep one buffer per camera stream.
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- CPU latency per call (ONNX Runtime, loaded machine): small 1248 ms window vs 381 ms streaming;
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dune 7537 ms vs 2021 ms.
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Re-export from the checkpoint with VisNavKit (add `streaming=true` for the streaming graph):
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```bash
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uv run visnavkit-export-dst checkpoint=flowpilot_dst_fastvit_t12.ckpt output=flowpilot_dst_fastvit_t12.onnx
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flowpilot-dst-dune/flowpilot_dst_dune_vitb14_streaming.inputs.npz
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version https://git-lfs.github.com/spec/v1
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oid sha256:49ca7ba15671aef8d5a0a52f96e990e4be08b2cda827c9f5cd677e6f0534663b
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size 1178476
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flowpilot-dst-dune/flowpilot_dst_dune_vitb14_streaming.metadata.json
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{
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"exp_name": "flowpilot_dune_dst_clips1k",
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"checkpoint": "logs/visnavkit/th7jpd4m/checkpoints/last.ckpt",
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"checkpoint_sha256": "1380b49fd47aa428a2070a169f8a1eab287c9bb45ac41a49adb796f1253eab7f",
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"onnx_sha256": "0504dace2478c3d89630ceafff31259d25869d013d1a0ab03d53078046708851",
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"precision": "float32",
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"opset": 17,
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"input_shapes": {
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"vision": [
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1,
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1,
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3,
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216,
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384
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],
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"route_patch": [
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1,
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1,
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80,
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80
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],
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"goal": [
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1,
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1,
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3
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+
],
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"ego": [
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| 28 |
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1,
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1,
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| 30 |
+
2
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| 31 |
+
],
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| 32 |
+
"action_bounds": [
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| 33 |
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1,
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| 34 |
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2,
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| 35 |
+
5
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| 36 |
+
],
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| 37 |
+
"feat_buffer": [
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1,
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19,
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2048
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+
],
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| 42 |
+
"buffer_mask": [
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1,
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| 44 |
+
19
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| 45 |
+
]
|
| 46 |
+
},
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| 47 |
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"output_shapes": {
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| 48 |
+
"modes": [
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1,
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| 50 |
+
6,
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| 51 |
+
80,
|
| 52 |
+
5
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| 53 |
+
],
|
| 54 |
+
"probs": [
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| 55 |
+
1,
|
| 56 |
+
6
|
| 57 |
+
],
|
| 58 |
+
"speed": [
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| 59 |
+
1,
|
| 60 |
+
1
|
| 61 |
+
],
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| 62 |
+
"feat_buffer_out": [
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| 63 |
+
1,
|
| 64 |
+
19,
|
| 65 |
+
2048
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| 66 |
+
],
|
| 67 |
+
"buffer_mask_out": [
|
| 68 |
+
1,
|
| 69 |
+
19
|
| 70 |
+
]
|
| 71 |
+
},
|
| 72 |
+
"streaming": true,
|
| 73 |
+
"pose_fields": [
|
| 74 |
+
"x_m",
|
| 75 |
+
"y_m",
|
| 76 |
+
"yaw_rad",
|
| 77 |
+
"v_mps",
|
| 78 |
+
"w_radps"
|
| 79 |
+
],
|
| 80 |
+
"target_times_s": [
|
| 81 |
+
0.05,
|
| 82 |
+
0.1,
|
| 83 |
+
0.15000000000000002,
|
| 84 |
+
0.2,
|
| 85 |
+
0.25,
|
| 86 |
+
0.30000000000000004,
|
| 87 |
+
0.35000000000000003,
|
| 88 |
+
0.4,
|
| 89 |
+
0.45,
|
| 90 |
+
0.5,
|
| 91 |
+
0.55,
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| 92 |
+
0.6000000000000001,
|
| 93 |
+
0.65,
|
| 94 |
+
0.7000000000000001,
|
| 95 |
+
0.75,
|
| 96 |
+
0.8,
|
| 97 |
+
0.8500000000000001,
|
| 98 |
+
0.9,
|
| 99 |
+
0.9500000000000001,
|
| 100 |
+
1.0,
|
| 101 |
+
1.05,
|
| 102 |
+
1.1,
|
| 103 |
+
1.1500000000000001,
|
| 104 |
+
1.2000000000000002,
|
| 105 |
+
1.25,
|
| 106 |
+
1.3,
|
| 107 |
+
1.35,
|
| 108 |
+
1.4000000000000001,
|
| 109 |
+
1.4500000000000002,
|
| 110 |
+
1.5,
|
| 111 |
+
1.55,
|
| 112 |
+
1.6,
|
| 113 |
+
1.6500000000000001,
|
| 114 |
+
1.7000000000000002,
|
| 115 |
+
1.75,
|
| 116 |
+
1.8,
|
| 117 |
+
1.85,
|
| 118 |
+
1.9000000000000001,
|
| 119 |
+
1.9500000000000002,
|
| 120 |
+
2.0,
|
| 121 |
+
2.0500000000000003,
|
| 122 |
+
2.1,
|
| 123 |
+
2.15,
|
| 124 |
+
2.2,
|
| 125 |
+
2.25,
|
| 126 |
+
2.3000000000000003,
|
| 127 |
+
2.35,
|
| 128 |
+
2.4000000000000004,
|
| 129 |
+
2.45,
|
| 130 |
+
2.5,
|
| 131 |
+
2.5500000000000003,
|
| 132 |
+
2.6,
|
| 133 |
+
2.6500000000000004,
|
| 134 |
+
2.7,
|
| 135 |
+
2.75,
|
| 136 |
+
2.8000000000000003,
|
| 137 |
+
2.85,
|
| 138 |
+
2.9000000000000004,
|
| 139 |
+
2.95,
|
| 140 |
+
3.0,
|
| 141 |
+
3.0500000000000003,
|
| 142 |
+
3.1,
|
| 143 |
+
3.1500000000000004,
|
| 144 |
+
3.2,
|
| 145 |
+
3.25,
|
| 146 |
+
3.3000000000000003,
|
| 147 |
+
3.35,
|
| 148 |
+
3.4000000000000004,
|
| 149 |
+
3.45,
|
| 150 |
+
3.5,
|
| 151 |
+
3.5500000000000003,
|
| 152 |
+
3.6,
|
| 153 |
+
3.6500000000000004,
|
| 154 |
+
3.7,
|
| 155 |
+
3.75,
|
| 156 |
+
3.8000000000000003,
|
| 157 |
+
3.85,
|
| 158 |
+
3.9000000000000004,
|
| 159 |
+
3.95,
|
| 160 |
+
4.0
|
| 161 |
+
],
|
| 162 |
+
"top_k": 6,
|
| 163 |
+
"noise": "zero",
|
| 164 |
+
"denoising_steps": 4,
|
| 165 |
+
"num_anchors": 64,
|
| 166 |
+
"parameters_total": 208170577,
|
| 167 |
+
"parity_max_abs_error": {
|
| 168 |
+
"modes": 1.430511474609375e-06,
|
| 169 |
+
"probs": 2.384185791015625e-07,
|
| 170 |
+
"speed": 0.0,
|
| 171 |
+
"feat_buffer_out": 4.410743713378906e-06,
|
| 172 |
+
"buffer_mask_out": 0.0
|
| 173 |
+
}
|
| 174 |
+
}
|
flowpilot-dst-dune/flowpilot_dst_dune_vitb14_streaming.onnx
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:0504dace2478c3d89630ceafff31259d25869d013d1a0ab03d53078046708851
|
| 3 |
+
size 829900699
|
flowpilot-dst-small/flowpilot_dst_fastvit_t12_streaming.inputs.npz
ADDED
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@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:eb225613cd0d9d90e4c87350c7e730719a601501c2d416d2e1df83e6b755722c
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| 3 |
+
size 2076524
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flowpilot-dst-small/flowpilot_dst_fastvit_t12_streaming.metadata.json
ADDED
|
@@ -0,0 +1,174 @@
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| 1 |
+
{
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| 2 |
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"exp_name": "flowpilot_dst_clips1k",
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| 3 |
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"checkpoint": "logs/visnavkit/jaz0uw1a/checkpoints/last.ckpt",
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| 4 |
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"checkpoint_sha256": "a45c6cf724ad4b70675f344ef94b6e809268dfff33f78497b8e1a7b446fdf6b8",
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"onnx_sha256": "f6d3e4e1b6cb90250e994bf66270f6887a10843fa2ccaebd896ee46d514c07c6",
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"precision": "float32",
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"goal": [
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"output_shapes": {
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},
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| 72 |
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"streaming": true,
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| 73 |
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"pose_fields": [
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| 74 |
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"x_m",
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| 75 |
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| 76 |
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| 77 |
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],
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}
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}
|
flowpilot-dst-small/flowpilot_dst_fastvit_t12_streaming.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f6d3e4e1b6cb90250e994bf66270f6887a10843fa2ccaebd896ee46d514c07c6
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| 3 |
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size 85721799
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