Add real eval subset (300 real cable imgs) as 'real' config

#2
by lw11 - opened
README.md CHANGED
@@ -19,6 +19,10 @@ configs:
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  data_files:
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  - split: train
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  path: data/*.parquet
 
 
 
 
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  ---
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  # WireSeg-36K
@@ -45,6 +49,7 @@ masks and per-image metric depth. Single category: `cable`. Generated with **Def
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  | path | what |
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  |---|---|
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  | `data/*.parquet` (config `default`) | RGB image + per-instance COCO-RLE masks + metadata, one row per image |
 
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  | `annotations.json` | full COCO ground truth (36,000 images / 176,387 annotations, single category `cable`) |
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  | `depth/*.tar.gz` | per-image metric depth, float32 `[1024,1024]` `.npy`, packed in 100 gzipped tar shards |
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@@ -80,10 +85,33 @@ d = np.load(f"depth/{ex['file_name'][:-4]}.npy") # float32 [1024,1024], metric
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  `jaccard_j`, `category`. Masks / bboxes / areas are JSON-encoded per-instance lists
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  (RLE = COCO compressed).
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  ## Splits
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- A single `train` split is provided; users should split as needed (recommended: stratify by
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- `scene_family` / `n_cable`).
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  ## Generation
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  data_files:
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  - split: train
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  path: data/*.parquet
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+ - config_name: real
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+ data_files:
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+ - split: test
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+ path: real/*.parquet
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  ---
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  # WireSeg-36K
 
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  | path | what |
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  |---|---|
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  | `data/*.parquet` (config `default`) | RGB image + per-instance COCO-RLE masks + metadata, one row per image |
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+ | `real/*.parquet` (config `real`) | **real-image eval subset** (300 imgs) — RGB + COCO-RLE masks, one row per image |
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  | `annotations.json` | full COCO ground truth (36,000 images / 176,387 annotations, single category `cable`) |
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  | `depth/*.tar.gz` | per-image metric depth, float32 `[1024,1024]` `.npy`, packed in 100 gzipped tar shards |
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  `jaccard_j`, `category`. Masks / bboxes / areas are JSON-encoded per-instance lists
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  (RLE = COCO compressed).
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+ ## Real eval subset (config `real`)
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+
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+ A companion set of **300 real cable images** with hand-verified ground truth, for evaluating
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+ sim-to-real transfer of the synthetic `default` set. These were cherry-picked as the
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+ **disagreement slice** between base **SAM 3** (prompt `"cable"`) and a cable-tuned **LoRA** —
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+ i.e. the images the two models most disagreed on, so they concentrate the hard/informative
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+ cases. Masks are COCO-RLE, single category `cable`.
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+
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+ - **Images:** 300 real (variable resolution) — `scene_family` = `real_easy` (224) / `real_hard` (76)
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+ - **Instances:** 2,119 cable masks (COCO RLE)
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+
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+ ```python
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+ from datasets import load_dataset
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+ real = load_dataset("DeformX/WireSeg-36K", "real", split="test")
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+ ex = real[0] # ex["image"] -> PIL.Image
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+ ```
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+
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+ Fields: `image`, `file_name`, `scene_family`, `masks_rle`, `bboxes`, `areas`, `num_instances`,
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+ `category`, `width`, `height` — the mask/bbox/area columns match the `default` config (same
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+ JSON-encoded per-instance COCO-RLE), so decoding code is shared. The synthetic-only QA columns
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+ (`n_cable`, `wire_area_frac`, `det_*`, `jaccard_j`) are omitted; `width`/`height` are added
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+ because real images are not a fixed size.
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+
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  ## Splits
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+ The `default` config provides a single `train` split; users should split as needed (recommended:
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+ stratify by `scene_family` / `n_cable`). The `real` config is a held-out `test` set.
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  ## Generation
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