| """Render the hero gallery: 4 sample images x (raw | cluster masks | berry keypoints).""" |
| import json |
| import sys |
| from pathlib import Path |
|
|
| import matplotlib |
|
|
| matplotlib.use("Agg") |
| import matplotlib.pyplot as plt |
| import numpy as np |
| import pandas as pd |
| from matplotlib.patches import Polygon |
| from PIL import Image |
|
|
| sys.path.insert(0, str(Path(__file__).resolve().parent)) |
| from vivid_utils import STYLE |
|
|
| ROOT = Path(__file__).resolve().parents[1] |
| DATA = ROOT / "data" |
| GRAPE_CATEGORY_ID = 1 |
| MASK_COLORS = ["#6366F1", "#F59E0B", "#10B981", "#EF4444", "#8B5CF6", "#06B6D4"] |
|
|
| |
| GALLERY_FILES = None |
|
|
|
|
| def pick_samples(meta): |
| if GALLERY_FILES: |
| return list(GALLERY_FILES) |
| picks = [] |
| pool = meta[meta.cluster_count.between(2, 8)].sort_values("berry_count") |
| for q in (0.15, 0.45, 0.7, 0.95): |
| row = pool.iloc[min(int(q * len(pool)), len(pool) - 1)] |
| if row.file_name not in picks: |
| picks.append(row.file_name) |
| return picks |
|
|
|
|
| def main(): |
| meta = pd.read_csv(DATA / "metadata.csv") |
| samples = pick_samples(meta) |
| print("gallery samples:", samples) |
|
|
| print("Loading COCO json...") |
| coco = json.loads((DATA / "anns" / "instances_updated.json").read_text()) |
| ids = {im["file_name"]: im["id"] for im in coco["images"] if im["file_name"] in samples} |
| polys = {name: [] for name in samples} |
| id_to_name = {v: k for k, v in ids.items()} |
| for ann in coco["annotations"]: |
| if ann["category_id"] != GRAPE_CATEGORY_ID or ann["image_id"] not in id_to_name: |
| continue |
| for seg in ann["segmentation"]: |
| pts = np.asarray(seg, dtype=float).reshape(-1, 2) |
| polys[id_to_name[ann["image_id"]]].append(pts) |
|
|
| fig, axes = plt.subplots(len(samples), 3, figsize=(9, 3.9 * len(samples)), |
| dpi=STYLE["dpi"], facecolor="white") |
| col_titles = ["image", "cluster masks", "berry keypoints"] |
| for r, name in enumerate(samples): |
| img = Image.open(DATA / "imgs" / name).convert("RGB") |
| img.thumbnail((900, 900)) |
| scale = img.width / meta.set_index("file_name").loc[name, "width"] |
| pts = np.load(DATA / "anns" / "points" / (Path(name).stem + ".npy")) * scale |
| for c in range(3): |
| ax = axes[r, c] |
| ax.imshow(img) |
| ax.set_xticks([]), ax.set_yticks([]) |
| for spine in ax.spines.values(): |
| spine.set_visible(False) |
| if r == 0: |
| ax.set_title(col_titles[c], fontsize=12, color=STYLE["text"]) |
| for i, poly in enumerate(polys[name]): |
| axes[r, 1].add_patch(Polygon(poly * scale, closed=True, alpha=0.45, |
| facecolor=MASK_COLORS[i % len(MASK_COLORS)], |
| edgecolor="white", linewidth=1.0)) |
| axes[r, 2].scatter(pts[:, 0], pts[:, 1], s=4, color="#FDE047", |
| edgecolors="#B45309", linewidths=0.3) |
| axes[r, 2].text(0.02, 0.02, f"{len(pts)} berries", transform=axes[r, 2].transAxes, |
| fontsize=11, fontweight="bold", color="white", |
| bbox=dict(facecolor="black", alpha=0.6, pad=3)) |
| fig.tight_layout() |
| out = ROOT / "assets" / "hero_gallery.png" |
| fig.savefig(out, dpi=STYLE["dpi"], facecolor="white", bbox_inches="tight") |
| print("wrote", out) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
