Download detectors/tiny-v2/metadata.json from tobil/omatrack-telemetry-models: direct link, hf CLI and curl.
- Browser
- Download file 4.36 kB
-
https://huggingface.co/tobil/omatrack-telemetry-models/resolve/main/detectors/tiny-v2/metadata.json
- Command line
-
hf download hf://tobil/omatrack-telemetry-models/detectors/tiny-v2/metadata.json
-
curl -L -o metadata.json https://huggingface.co/tobil/omatrack-telemetry-models/resolve/main/detectors/tiny-v2/metadata.json
4.36 kB
| { | |
| "schema": "gauge-detector-center-v1", | |
| "model_file": "gauge-detector.onnx", | |
| "model_sha256": "99bdd483402444e8c799452d9885c1184980a41f2cd80d4af4d7a6b3ae00abc6", | |
| "model_bytes": 966419, | |
| "contract_file": "contract.json", | |
| "contract_sha256": "87a4cec9e0466250b635e561c74be81f2ce5f15fbd79804a1be639c3719a69d3", | |
| "checkpoint_sha256": "42fca6a5cad028bd21c7a05195c93c02597f8ffe2c5280875a5f1254029c0f83", | |
| "selected_epoch": 7, | |
| "frozen_config_sha256": "a58dcdd47804b38eb2dfeccce12f43f570628bf82117ccdf62975b16a0244280", | |
| "parameters": 237142, | |
| "onnx_opset": 17, | |
| "operators": [ | |
| "Add", | |
| "Cast", | |
| "Concat", | |
| "Constant", | |
| "Conv", | |
| "Div", | |
| "Gather", | |
| "GlobalAveragePool", | |
| "HardSigmoid", | |
| "HardSwish", | |
| "Mul", | |
| "Relu", | |
| "Resize", | |
| "Shape", | |
| "Slice", | |
| "Sub", | |
| "Unsqueeze" | |
| ], | |
| "onnx_version": "1.19.1", | |
| "ort_version": "1.24.2", | |
| "status": "experimental_candidate_not_independently_accepted", | |
| "input": { | |
| "name": "image", | |
| "dtype": "float32", | |
| "layout": "NCHW", | |
| "shape": [ | |
| 1, | |
| 3, | |
| 384, | |
| 640 | |
| ], | |
| "channels": "RGB", | |
| "range": [ | |
| 0, | |
| 1 | |
| ], | |
| "spatial_multiple": 32, | |
| "dynamic_spatial": true, | |
| "resize": "stretch_full_source_half_pixel_bilinear_no_antialias", | |
| "pixel_formula": "sx=(dx+0.5)*source_width/dest_width-0.5; sy analogous; floor coordinates, clamp each neighbor index; interpolate raw uint8 RGB in float32 then divide by 255; no intermediate uint8 rounding", | |
| "normalization": "divide_255_only; ImageNet normalization is inside the graph" | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "center_logits", | |
| "channels": 1 | |
| }, | |
| { | |
| "name": "size_logits", | |
| "channels": 2, | |
| "order": [ | |
| "width", | |
| "height" | |
| ] | |
| }, | |
| { | |
| "name": "offset_logits", | |
| "channels": 2, | |
| "order": [ | |
| "x", | |
| "y" | |
| ] | |
| }, | |
| { | |
| "name": "representation_logits", | |
| "channels": 4, | |
| "labels": [ | |
| "digits", | |
| "bar", | |
| "wheel", | |
| "needle" | |
| ] | |
| }, | |
| { | |
| "name": "semantic_logits", | |
| "channels": 5, | |
| "labels": [ | |
| "unknown", | |
| "gear", | |
| "stint_lap", | |
| "brake", | |
| "throttle" | |
| ] | |
| } | |
| ], | |
| "decode": { | |
| "score_threshold": 0.35, | |
| "local_max_kernel": 3, | |
| "local_max_rule": "sigmoid(center) >= every in-bounds 3x3 neighbor; equal maxima all retained before top-k", | |
| "candidate_limit": 100, | |
| "sort": "descending score then ascending flat y*grid_width+x index", | |
| "center": "((x+sigmoid(offset_x))/grid_width,(y+sigmoid(offset_y))/grid_height)", | |
| "size": "(sigmoid(width_logit),sigmoid(height_logit)) normalized full-source width/height", | |
| "box": "center +/- size/2; clip each coordinate to [0,1]; discard zero-area", | |
| "nms": "class-agnostic greedy suppress IoU strictly > 0.4", | |
| "nms_iou": 0.4, | |
| "max_detections": 32, | |
| "representation": "argmax; lowest index wins ties", | |
| "semantic": "softmax argmax; lowest index wins ties; emit unknown if max probability < 0.8", | |
| "semantic_threshold": 0.8 | |
| }, | |
| "limitations": [ | |
| "scores are not calibrated probabilities", | |
| "unknown semantic has positive supervision only for explicitly observed non-Tier1 fields in four TRAIN images; ambiguous fields and generic lap-counter ownership remain masked; no open-set certification", | |
| "all synthetic semantic loss fully masked; no renderer-intent labels", | |
| "real weak windows use positive MIL only, no extent or offset loss or background negatives; four pixel-reviewed TRAIN images provide stronger geometry with explicit ignored regions", | |
| "bar includes segmented indicators, no fill direction or scale predicted", | |
| "visibility/readability/support remain unknown", | |
| "detector boxes never imply arbitrary crop reader support", | |
| "confirmed user/reviewed configuration required before extraction", | |
| "only two known real layouts and four reviewed TRAIN background assets; repeated views are not new source diversity" | |
| ], | |
| "licensing": "torchvision BSD-3-Clause backbone; task weights redistribution license unspecified; no public upload", | |
| "required_metadata_keys": [ | |
| "schema", | |
| "model_file", | |
| "model_sha256", | |
| "contract_file", | |
| "contract_sha256", | |
| "status", | |
| "input", | |
| "outputs", | |
| "decode", | |
| "limitations" | |
| ] | |
| } | |