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code/prepare_images.py

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+"""
+Prepare images for COLMAP SfM + 3DGS.
+- Convert RGBA -> RGB on white background
+- Resize so max dimension <= 1600 (COLMAP works better with reasonable res)
+- Organize into per-part input folders: data/parts/<part>/input/*.png
+"""
+import os
+from PIL import Image
+import numpy as np
+
+SRC = "data/raw"
+DST = "data/parts"
+MAX_DIM = 1600
+
+os.makedirs(DST, exist_ok=True)
+
+for part in sorted(os.listdir(SRC)):
+    src_dir = os.path.join(SRC, part)
+    if not os.path.isdir(src_dir):
+        continue
+    dst_dir = os.path.join(DST, part, "input")
+    os.makedirs(dst_dir, exist_ok=True)
+    for fname in sorted(os.listdir(src_dir)):
+        if not fname.lower().endswith(".png"):
+            continue
+        im = Image.open(os.path.join(src_dir, fname)).convert("RGBA")
+        arr = np.array(im)
+        # composite over white background
+        alpha = arr[:, :, 3:4].astype(np.float32) / 255.0
+        rgb = arr[:, :, :3].astype(np.float32)
+        bg = np.array([255, 255, 255], dtype=np.float32)
+        composited = rgb * alpha + bg * (1 - alpha)
+        out = Image.fromarray(composited.astype(np.uint8), "RGB")
+        # resize
+        w, h = out.size
+        scale = MAX_DIM / max(w, h)
+        if scale < 1.0:
+            nw, nh = int(w * scale), int(h * scale)
+            out = out.resize((nw, nh), Image.LANCZOS)
+        # rename to simple sequential
+        idx = fname.split("_")[-1].split(".")[0]
+        out_name = f"{part}_{idx}.png"
+        out.save(os.path.join(dst_dir, out_name))
+        print(f"{part}/{fname} -> {out_name} {out.size}")
+
+print("Done preparing images.")