From 9b9fb0eb840dceb204dc20e7dc36cc15328c8df2 Mon Sep 17 00:00:00 2001
From: SPACEBROWSER_DEV <developer@thespacebrowser.com>
Date: Wed, 8 Oct 2025 02:42:25 +0000
Subject: [PATCH] Pano To Cube Light

---
 panotocube_light_fast.py | 89 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 89 insertions(+)
 create mode 100644 panotocube_light_fast.py

diff --git a/panotocube_light_fast.py b/panotocube_light_fast.py
new file mode 100644
index 0000000..6768444
--- /dev/null
+++ b/panotocube_light_fast.py
@@ -0,0 +1,89 @@
+import os, cv2, numpy as np
+from concurrent.futures import ProcessPoolExecutor, as_completed
+
+# ---- geometry: build remap grids once per (src_w, src_h, face_size) ----
+def build_cubemap_luts(src_w, src_h, face_size):
+    faces = ["right", "left", "front", "back"]
+    luts = {}
+
+    # normalized pixel grid (u,v) in [0,1]
+    ys, xs = np.meshgrid(
+        (np.arange(face_size) + 0.5) / face_size,
+        (np.arange(face_size) + 0.5) / face_size,
+        indexing="ij"
+    )
+    a = 2.0 * xs - 1.0
+    b = 2.0 * ys - 1.0
+
+    # direction vectors for each face (no Python loops)
+    dirs = {
+        "right":  np.stack([ np.ones_like(a),  b,        -a       ], axis=-1),
+        "left":   np.stack([-np.ones_like(a),  b,         a       ], axis=-1),
+        "front":  np.stack([        a,         b,  np.ones_like(a)], axis=-1),
+        "back":   np.stack([       -a,         b, -np.ones_like(a)], axis=-1),
+    }
+
+    for face, d in dirs.items():
+        # normalize
+        n = np.linalg.norm(d, axis=-1, keepdims=True)
+        d = d / n
+
+        # spherical (theta: -pi..pi, phi: -pi/2..pi/2)
+        theta = np.arctan2(d[..., 2], d[..., 0])
+        phi   = np.arcsin(d[..., 1])
+
+        # equirect UV in [0,1]
+        uf = 0.5 * (theta / np.pi + 1.0)
+        vf = 0.5 * (phi / (np.pi / 2) + 1.0)
+
+        # convert to source pixel coords (wrap horizontally!)
+        map_x = (uf * (src_w - 1)).astype(np.float32)
+        map_y = ((1.0 - vf) * (src_h - 1)).astype(np.float32)
+
+        # IMPORTANT: wrap horizontally to avoid seams at 0/360
+        map_x = np.mod(map_x, src_w).astype(np.float32)
+
+        luts[face] = (map_x, map_y)
+
+    return luts
+
+def process_image(path_in, out_dir, face_size, luts):
+    img = cv2.imread(path_in, cv2.IMREAD_COLOR)
+    if img is None:
+        return f"Skipped (read error): {path_in}"
+
+    h, w = img.shape[:2]
+    base = os.path.splitext(os.path.basename(path_in))[0]
+
+    for face, (mx, my) in luts.items():
+        face_img = cv2.remap(
+            img, mx, my,
+            interpolation=cv2.INTER_LINEAR,
+            borderMode=cv2.BORDER_WRAP,  # seamless horizontally
+        )
+        face_img = cv2.rotate(face_img, cv2.ROTATE_180)
+        cv2.imwrite(os.path.join(out_dir, f"{base}_{face}.jpg"), face_img)
+
+    return f"Done: {base}"
+
+def main(input_dir='FRAMES', output_dir='cubemaps', face_size=1024, workers= max(1, os.cpu_count()-1)):
+    os.makedirs(output_dir, exist_ok=True)
+
+    # peek one frame to get source size
+    sample = next((f for f in sorted(os.listdir(input_dir)) if f.lower().endswith((".jpg",".jpeg",".png"))), None)
+    assert sample, "No input frames found."
+    sample_img = cv2.imread(os.path.join(input_dir, sample))
+    h, w = sample_img.shape[:2]
+
+    # precompute LUTs once
+    luts = build_cubemap_luts(w, h, face_size)
+
+    # batch process (parallel)
+    files = [os.path.join(input_dir, f) for f in sorted(os.listdir(input_dir)) if f.lower().endswith((".jpg",".jpeg",".png"))]
+    with ProcessPoolExecutor(max_workers=workers) as ex:
+        futures = [ex.submit(process_image, p, output_dir, face_size, luts) for p in files]
+        for _ in as_completed(futures):
+            pass  # keep silent; or print(_) to see progress
+
+if __name__ == "__main__":
+    main()