Datasets:
Download src/explicit_learning/certificates/plot_observation.py from sungguk/visual-answerability: direct link, hf CLI and curl.
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- Download file 2.02 kB
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https://huggingface.co/datasets/sungguk/visual-answerability/resolve/main/src/explicit_learning/certificates/plot_observation.py
- Command line
-
hf download hf://datasets/sungguk/visual-answerability/src/explicit_learning/certificates/plot_observation.py
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curl -L -o plot_observation.py https://huggingface.co/datasets/sungguk/visual-answerability/resolve/main/src/explicit_learning/certificates/plot_observation.py
2.02 kB
| """Direct PlotQA observation comparisons, without digest validation. | |
| These are the production drawing primitives. They are not an independent | |
| renderer; independence applies to the two semantic executors only. | |
| """ | |
| from __future__ import annotations | |
| import copy | |
| import io | |
| from pathlib import Path | |
| _FONT_READY = False | |
| def pixels(blob): | |
| import numpy as np | |
| from PIL import Image | |
| return np.asarray(Image.open(io.BytesIO(blob)).convert("RGBA")) | |
| def render_direct(world, manifest): | |
| global _FONT_READY | |
| import matplotlib | |
| matplotlib.use("Agg") | |
| from matplotlib import font_manager | |
| from explicit_learning.renderers import plot | |
| if not _FONT_READY: | |
| root = Path(matplotlib.get_data_path()) / "fonts" / "ttf" | |
| for name in ("DejaVuSans.ttf", "DejaVuSerif.ttf"): | |
| font_manager.fontManager.addfont(root / name) | |
| _FONT_READY = True | |
| family = plot.PLOT_FAMILIES[manifest["renderer_id"]] | |
| series = plot._parse_series(world) | |
| domain = plot._build_domain(world, series) | |
| canvas = plot._Canvas(manifest["width"], manifest["height"], family) | |
| visible = plot._draw_plot(canvas, world, series, domain, family) | |
| image, owners, counts = canvas.finish() | |
| glyphs = [ | |
| {"node_id": g.node_id, "text": g.text, "bbox": [g.x0, g.y0, g.x1, g.y1]} | |
| for g in sorted(canvas.glyphs, key=lambda x: (x.node_id, x.text, x.x0, x.y0)) | |
| ] | |
| return { | |
| "image": image, | |
| "owners": owners, | |
| "glyphs": glyphs, | |
| "node_table": ["__background__", *canvas.owner_ids], | |
| "coverage": {n: counts.get(n, 0) for n in sorted(visible)}, | |
| "domain": domain.manifest_record(), | |
| } | |
| def visible_projection(world): | |
| world = copy.deepcopy(world) | |
| hidden = {n for n, flag in world.get("_node_visibility", {}).items() if flag == "hidden"} | |
| for series in world.get("series", []): | |
| for point in series.get("points", []): | |
| if point["id"] in hidden: | |
| point["y"] = None | |
| return world | |