#!/usr/bin/env python3
"""Encode the NEURAL-KEYFRAME inter-frame video: the I-frame is decoded by the
integer learned codec `int_hyper`, and the P-frames are integer block-MC residuals
on top — the whole decode integer, byte-exact on every machine.

The I-frame here is the committed tiny `int_hyper` vector (so the conformance is
self-contained and never-skips); the P-frames translate it and code the residual.
The Rust decoder composes `int_hyper_synth::decode_conditional_checked` (frame 0) with
`int_video::decode_pframes` (the rest) — this script emits only the P-frame
bitstream + the expected per-frame / clip hashes (frame 0's hash is int_hyper's).

  python tools/wai_int_video_keyframe_encode.py <int_hyper-vectors-dir> <out-dir>
"""
import sys, os, json, base64, tempfile
import numpy as np
from compressai.ans import RansEncoder

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from wai_int_hyper_tiny_vector import main as gen_tiny

BLOCK, SEARCH, Q, NF = 8, 4, 6, 5


def fnv1a(buf):
    h = 14695981039346656037
    for b in buf:
        h = ((h ^ b) * 1099511628211) & 0xFFFFFFFFFFFFFFFF
    return h


def laplacian_cdf(rmax):
    n = 2 * rmax + 1
    pmf = np.exp(-np.abs(np.arange(n) - rmax) / 6.0)
    total = 1 << 16
    f = np.maximum((pmf / pmf.sum() * (total - 1)).round().astype(np.int64), 1)
    f[f.argmax()] += (total - 1) - int(f.sum())
    cdf = [0]
    for v in f:
        cdf.append(cdf[-1] + int(v))
    cdf.append(total)
    return cdf


def mc_predict(ref, mvs, h, w):
    pred = np.empty_like(ref)
    nbx = (w + BLOCK - 1) // BLOCK
    for by in range(0, h, BLOCK):
        for bx in range(0, w, BLOCK):
            dy, dx = mvs[(by // BLOCK) * nbx + (bx // BLOCK)]
            for y in range(by, min(by + BLOCK, h)):
                sy = min(max(y + dy, 0), h - 1)
                for x in range(bx, min(bx + BLOCK, w)):
                    pred[y, x] = ref[sy, min(max(x + dx, 0), w - 1)]
    return pred


def search_mvs(cur, ref, h, w):
    mvs = []
    for by in range(0, h, BLOCK):
        for bx in range(0, w, BLOCK):
            cb = cur[by:by + BLOCK, bx:bx + BLOCK]
            best, bmv = None, (0, 0)
            for dy in range(-SEARCH, SEARCH + 1):
                for dx in range(-SEARCH, SEARCH + 1):
                    ys = np.clip(np.arange(by, by + cb.shape[0]) + dy, 0, h - 1)
                    xs = np.clip(np.arange(bx, bx + cb.shape[1]) + dx, 0, w - 1)
                    sad = int(np.abs(cb - ref[np.ix_(ys, xs)]).sum())
                    if best is None or sad < best:
                        best, bmv = sad, (dy, dx)
            mvs.append([int(bmv[0]), int(bmv[1])])
    return mvs


def main(ih_dir, outdir):
    os.makedirs(outdir, exist_ok=True)
    # frame 0 = the int_hyper I-frame (regenerate the tiny vector in a temp dir to
    # read its decoded pixels; the committed int_hyper vector itself is untouched).
    with tempfile.TemporaryDirectory() as tmp:
        rgb0, H, W = gen_tiny(tmp)
    frame0 = rgb0.astype(np.int64)           # HWC int, 0..255
    rmax = (255 + Q - 1) // Q
    cdf, offset = laplacian_cdf(rmax), -rmax

    frames = [frame0] + [np.roll(frame0, (f, f), axis=(0, 1)) for f in range(1, NF)]  # translate
    recon, mvs_all, syms, hashes = [frame0], [[]], [], []
    hashes.append(format(fnv1a(np.ascontiguousarray(frame0.astype(np.uint8)).tobytes()), '016x'))
    for f in range(1, NF):
        mvs = search_mvs(frames[f], recon[-1], H, W)
        pred = np.stack([mc_predict(recon[-1][..., c], mvs, H, W) for c in range(3)], -1)
        rq = np.round((frames[f] - pred) / Q).astype(np.int64).clip(-rmax, rmax)
        syms.extend(rq.reshape(-1).tolist())
        rec = np.clip(pred + rq * Q, 0, 255).astype(np.int64)
        recon.append(rec)
        mvs_all.append(mvs)
        hashes.append(format(fnv1a(np.ascontiguousarray(rec.astype(np.uint8)).tobytes()), '016x'))

    bits = RansEncoder().encode_with_indexes(syms, [0] * len(syms), [cdf], [len(cdf)], [offset])
    clip_hash = format(fnv1a(b''.join(bytes.fromhex(h) for h in hashes)), '016x')
    json.dump({'block': BLOCK, 'q': Q, 'rmax': rmax, 'offset': offset, 'cdf': cdf,
               'n_frames': NF, 'h': H, 'w': W, 'mvs': mvs_all,
               'rans_b64': base64.b64encode(bytes(bits)).decode()},
              open(f'{outdir}/video_nk_bitstream.json', 'w'))
    json.dump({'n_frames': NF, 'h': H, 'w': W, 'frame_hashes': hashes, 'clip_hash': clip_hash},
              open(f'{outdir}/video_nk.json', 'w'))
    print(f'int_hyper-keyframe video: {NF}x {H}x{W} (I-frame={hashes[0]}), {len(bits)} P rANS bytes '
          f'-> clip_hash {clip_hash}')


if __name__ == '__main__':
    main(sys.argv[1], sys.argv[2])