#!/usr/bin/env python3
"""
Cylindrical panorama stitch.

North faces ~0° azimuth, sunrise faces ~90°.  Project both onto the same
cylinder so the NE overlap region appears at the same y-coordinate in both
and the scene is geometrically continuous.

Usage:
  python3 stitch_cyl.py north.jpg sunrise.jpg out_prefix [focal_px]
  focal_px defaults to 1920 (= ~90° HFOV at 3840 px wide).
  Try 1300-1920 to span 90°-120° HFOV.
"""
import sys, cv2, numpy as np

north_p  = sys.argv[1]
sunrise_p= sys.argv[2]
prefix   = sys.argv[3]
f        = float(sys.argv[4]) if len(sys.argv) > 4 else 1920.0

north   = cv2.imread(north_p)
sunrise = cv2.imread(sunrise_p)
H, W = north.shape[:2]
cx, cy = W / 2.0, H / 2.0
print(f"Images: {W}x{H}   focal estimate: {f:.0f} px")

# ── Cylindrical projection ────────────────────────────────────────────────────
# Maps output (cylindrical) pixel (xc, yc) ← input (flat) pixel (xs, ys):
#   theta  = xc / f              (horizontal angle from optical axis)
#   xs     = f * tan(theta) + cx
#   ys     = yc / cos(theta) + cy
def cylindrical_warp(img, f, cx, cy):
    h, w = img.shape[:2]
    xc = np.arange(w, dtype=np.float32) - cx
    yc = np.arange(h, dtype=np.float32) - cy
    XC, YC = np.meshgrid(xc, yc)
    theta  = XC / f
    map_x  = (f * np.tan(theta) + cx).astype(np.float32)
    map_y  = (YC / np.cos(theta) + cy).astype(np.float32)
    return cv2.remap(img, map_x, map_y, cv2.INTER_LINEAR,
                     borderMode=cv2.BORDER_CONSTANT, borderValue=0)

n_cyl = cylindrical_warp(north,   f, cx, cy)
s_cyl = cylindrical_warp(sunrise, f, cx, cy)

cv2.imwrite(f"{prefix}-north-cyl.jpg",   n_cyl)
cv2.imwrite(f"{prefix}-sunrise-cyl.jpg", s_cyl)
print("Cylindrical projections saved.")

# ── Phase-correlate on the treeline band of the cylindrical images ────────────
y0, y1 = int(H * 0.70), int(H * 0.90)
ow = int(W * 0.30)               # look in outer 30% of each image
n_strip = cv2.cvtColor(n_cyl[:, W-ow:], cv2.COLOR_BGR2GRAY)[y0:y1].astype(np.float64)
s_strip = cv2.cvtColor(s_cyl[:, :ow],   cv2.COLOR_BGR2GRAY)[y0:y1].astype(np.float64)

# Normalised cross-power spectrum (phase correlation)
N  = np.fft.fft2(n_strip)
S  = np.fft.fft2(s_strip)
R  = N * np.conj(S)
nrm = np.abs(R); nrm[nrm == 0] = 1
corr = np.fft.ifft2(R / nrm).real
peak = np.unravel_index(np.argmax(corr), corr.shape)
dy_r, dx_r = peak
rh, rw = corr.shape
if dy_r > rh // 2: dy_r -= rh
if dx_r > rw // 2: dx_r -= rw
print(f"Phase-corr (cylindrical): dx={dx_r}  dy={dy_r}")

# Convert from band-strip offsets to full-image translation
tx = -(W - ow + dx_r)   # how far left north sits relative to sunrise
ty = -dy_r
print(f"Translation:  tx={tx}  ty={ty}")

# ── Build panorama from cylindrical images ───────────────────────────────────
xmin = min(0, tx);  ymin = min(0, ty)
xmax = max(W, W+tx); ymax = max(H, H+ty)
cW = int(xmax-xmin); cH = int(ymax-ymin)
sx0, sy0 = int(-xmin), int(-ymin)   # sunrise origin
nx0, ny0 = sx0+tx,  sy0+ty          # north origin
nx0, ny0 = int(nx0), int(ny0)
print(f"Canvas: {cW}x{cH}")

canvas = np.zeros((cH, cW, 3), dtype=np.uint8)
# North first (background)
canvas[ny0:ny0+H, nx0:nx0+W] = n_cyl
# Sunrise on top (base image)
canvas[sy0:sy0+H, sx0:sx0+W] = s_cyl

# Feathered blend in overlap
ov_x0 = max(sx0, nx0);  ov_x1 = min(sx0+W, nx0+W)
ov_y0 = max(sy0, ny0);  ov_y1 = min(sy0+H, ny0+H)
if ov_x1 > ov_x0 and ov_y1 > ov_y0:
    ov_w = ov_x1 - ov_x0
    alpha = np.linspace(0.0, 1.0, ov_w, dtype=np.float32)[np.newaxis, :, np.newaxis]
    n_patch = n_cyl[ov_y0-ny0:ov_y1-ny0, ov_x0-nx0:ov_x1-nx0].astype(np.float32)
    s_patch = s_cyl[ov_y0-sy0:ov_y1-sy0, ov_x0-sx0:ov_x1-sx0].astype(np.float32)
    canvas[ov_y0:ov_y1, ov_x0:ov_x1] = (s_patch*alpha + n_patch*(1-alpha)).astype(np.uint8)
    print(f"Overlap blend: {ov_w}x{ov_y1-ov_y0}px")

# Crop black margin from ty offset
top  = max(sy0, ny0)
bot  = min(sy0+H, ny0+H)
canvas = canvas[top:bot, :]

cv2.imwrite(f"{prefix}-panorama.jpg", canvas, [cv2.IMWRITE_JPEG_QUALITY, 92])
preview = cv2.resize(canvas, (canvas.shape[1]//2, canvas.shape[0]//2))
cv2.imwrite(f"{prefix}-preview.jpg", preview, [cv2.IMWRITE_JPEG_QUALITY, 88])
print(f"Panorama → {prefix}-panorama.jpg  ({canvas.shape[1]}x{canvas.shape[0]})")