hdf5 support

backend/importers/array_image.py

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+"""
+Importer for pixel images (PNG, TIFF, JPEG, BMP) and NumPy arrays (.npy, .npz).
+These formats carry no physical calibration, so calibrated = False.
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+import numpy as np
+
+from backend.data_types import DataField
+
+
+extensions = frozenset({".png", ".jpg", ".jpeg", ".tiff", ".tif", ".bmp", ".npy", ".npz"})
+calibrated = False
+
+
+def load(path: Path) -> list[DataField]:
+    ext = path.suffix.lower()
+
+    if ext == ".npy":
+        arr = np.load(str(path)).astype(np.float64)
+    elif ext == ".npz":
+        npz = np.load(str(path))
+        key = list(npz.files)[0]
+        arr = npz[key].astype(np.float64)
+    else:
+        from PIL import Image as PILImage
+        img = PILImage.open(str(path))
+        arr = np.array(img)
+        if arr.dtype != np.uint8:
+            arr = arr.astype(np.float64)
+
+    if arr.ndim == 3:
+        gray = np.mean(arr.astype(np.float64), axis=2)
+    else:
+        gray = arr.astype(np.float64)
+
+    return [DataField(data=gray)]
+
+
+def channel_names(path: Path) -> list[str]:
+    return ["field"]