| """Show a stimulus (image, prompt, segmentation) or a whole minimal pair. |
| |
| python scripts/visualize.py S46 # one stimulus |
| python scripts/visualize.py X-REL-CAT-LEFT-DOG-RICH # every member of a pair, side by side |
| python scripts/visualize.py S46 --out s46.png # save instead of opening a window |
| python scripts/visualize.py --list # list the stimuli and the pairs |
| |
| Objects named in the prompt are outlined in green, unmentioned ones in orange, negated ones |
| ("with no lamp") in purple; background regions (sky, wall, floor...) are labelled in grey. |
| |
| Run it from a local copy of the dataset (git clone, or huggingface_hub.snapshot_download), or point |
| --root at one. Needs: pip install matplotlib pillow numpy |
| """ |
| import argparse |
| import json |
| import sys |
| import textwrap |
| from pathlib import Path |
|
|
| import numpy as np |
| from PIL import Image |
|
|
| STATUS = {"mentioned": "#2e9e44", "unmentioned": "#e07b00", "negated": "#8e44ad", "background": "#7f7f7f"} |
|
|
|
|
| def load(root): |
| rows = [json.loads(l) for l in open(root / "data" / "metadata.jsonl", encoding="utf-8") if l.strip()] |
| pairs = [json.loads(l) for l in open(root / "pairs" / "pairs.jsonl", encoding="utf-8") if l.strip()] |
| return {r["sample_id"]: r for r in rows}, {p["pair_id"]: p for p in pairs} |
|
|
|
|
| def segment_ids(root, row): |
| seg = np.asarray(Image.open(root / row["segmentation"]).convert("RGB"), dtype=np.uint32) |
| return seg[..., 0] + 256 * seg[..., 1] + 256 ** 2 * seg[..., 2] |
|
|
|
|
| def status(obj, stuff_ids): |
| if obj["negated"]: |
| return "negated" |
| if obj["mentioned"]: |
| return "mentioned" |
| return "background" if obj["segment_id"] in stuff_ids else "unmentioned" |
|
|
|
|
| def draw(ax_img, ax_seg, root, row, role=None): |
| import matplotlib.patches as patches |
|
|
| image = np.asarray(Image.open(root / "data" / row["file_name"]).convert("RGB")) |
|
|
| title = f'{row["sample_id"]}{f" ({role})" if role else ""}: "{row["prompt"]}"' |
| ax_img.imshow(image) |
| ax_img.set_title(textwrap.fill(title, 75), fontsize=10) |
| if row.get("control_type"): |
| sub = f'control [{row["control_type"]}]' |
| else: |
| sub = f'{row["case_id"]} {row["subcategory"]}' + (f' [{row["case_variant"]}]' if row.get("case_variant") else "") |
| ax_img.set_xlabel(textwrap.fill(f"{sub}. Unmentioned: {row['unmentioned_content']}", 80), fontsize=8) |
| for ax in (ax_img, ax_seg): |
| ax.set_xticks([]) |
| ax.set_yticks([]) |
|
|
| if not row.get("segmentation"): |
| ax_seg.axis("off") |
| text = row.get("description") or "(no segmentation)" |
| if row.get("generation_prompt"): |
| text += f'\n\nGeneration prompt ({row["image_source"]}, seed {row.get("generation_seed")}): {row["generation_prompt"]}' |
| ax_seg.text(0, 1, textwrap.fill(text, 70, replace_whitespace=False), va="top", fontsize=8, wrap=True) |
| return |
|
|
| ids = segment_ids(root, row) |
| info = json.load(open((root / row["segmentation"]).with_suffix(".json"), encoding="utf-8"))["segments_info"] |
| stuff_ids = {s["id"] for s in info if not s["isthing"]} |
| rng = np.random.default_rng(0) |
| overlay = image.astype(float) * 0.35 |
| for obj in row["objects"]: |
| m = ids == obj["segment_id"] |
| overlay[m] += rng.integers(60, 255, 3) * 0.65 |
| ax_seg.imshow(overlay.clip(0, 255).astype(np.uint8)) |
| ax_seg.set_title("segmentation", fontsize=10) |
| for obj in row["objects"]: |
| st = status(obj, stuff_ids) |
| x, y, w, h = obj["bbox"] |
| if st != "background": |
| ax_seg.add_patch(patches.Rectangle((x, y), w, h, fill=False, edgecolor=STATUS[st], linewidth=1.8)) |
| ax_seg.text(x + 3, y + 14, obj["label"], fontsize=7, color="white", |
| bbox=dict(facecolor=STATUS[st], edgecolor="none", pad=1.2, alpha=0.9)) |
|
|
|
|
| def main(): |
| p = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) |
| p.add_argument("id", nargs="?", help="a sample_id (S46) or a pair_id (P-C2, X-REL-...)") |
| p.add_argument("--root", type=Path, default=Path(__file__).resolve().parent.parent, help="dataset folder") |
| p.add_argument("--out", type=Path, help="save the figure to this file instead of showing it") |
| p.add_argument("--list", action="store_true", help="list the stimuli and the pairs") |
| args = p.parse_args() |
|
|
| samples, pairs = load(args.root) |
| if args.list or not args.id: |
| for s in samples.values(): |
| print(f'{s["sample_id"]:5} {s["case_id"] or "ctl":3} "{s["prompt"]}"') |
| print() |
| for pr in pairs.values(): |
| print(f'{pr["pair_id"]:30} {pr["axis"]:6} {pr["family_expected"]:11} {", ".join(m["sample_id"] for m in pr["members"])}') |
| return |
|
|
| import matplotlib |
| if args.out: |
| matplotlib.use("Agg") |
| import matplotlib.pyplot as plt |
| from matplotlib.lines import Line2D |
|
|
| if args.id in samples: |
| members, title = [(samples[args.id], None)], None |
| elif args.id in pairs: |
| pr = pairs[args.id] |
| members = [(samples[m["sample_id"]], m["role"]) for m in pr["members"]] |
| title = f'{pr["pair_id"]}: same {"prompt" if pr["axis"] == "image" else "image"}, ' \ |
| f'expected {pr["family_expected"]}' |
| else: |
| sys.exit(f"unknown id {args.id!r} (try --list)") |
|
|
| fig, axes = plt.subplots(len(members), 2, figsize=(11, 3.9 * len(members) + 0.4), squeeze=False) |
| for (row, role), (ax_img, ax_seg) in zip(members, axes): |
| draw(ax_img, ax_seg, args.root, row, role) |
| legend = [Line2D([0], [0], color=c, lw=4, label=k) for k, c in STATUS.items()] |
| fig.legend(handles=legend, loc="lower center", ncol=4, fontsize=8, frameon=False) |
| if title: |
| fig.suptitle(title, fontsize=11) |
| fig.tight_layout(rect=(0, 0.06 / len(members), 1, 1 - 0.04 / len(members) if title else 1)) |
| if args.out: |
| fig.savefig(args.out, dpi=110) |
| print(f"saved {args.out}") |
| else: |
| plt.show() |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
