scripts/phase4_render.py

import csv
import json
import os

import cv2
import numpy as np

ROOT = "/root/bdmc_pipeline"
FRAMES_DIR = f"{ROOT}/frames"
MASKS_DIR = f"{ROOT}/masks/road_surface"
DEPTH_DIR = f"{ROOT}/depth"
OUT_DIR = f"{ROOT}/outputs"
FPS = 5.0
H, W = 1920, 1080
FOV_LONG_DEG = 72.0
fx = fy = H / (2 * np.tan(np.radians(FOV_LONG_DEG / 2)))
N_FRAMES = 300

os.makedirs(OUT_DIR, exist_ok=True)

defects = []
defects_path = f"{OUT_DIR}/defects_fused.csv"
if os.path.exists(defects_path):
    with open(defects_path) as f:
        reader = csv.DictReader(f)
        for row in reader:
            if row.get("confidence") in ("agree", "partial"):
                defects.append(row)

devmaps = None
devmaps_path = f"{OUT_DIR}/devmaps_small.npz"
if os.path.exists(devmaps_path):
    z = np.load(devmaps_path)
    devmaps = z["dev"].astype(np.float32)
    devmaps = (devmaps - 128.0) / 1000.0

fourcc = cv2.VideoWriter_fourcc(*"mp4v")
out_path = f"{OUT_DIR}/overlay_60s.mp4"
writer = cv2.VideoWriter(out_path, fourcc, FPS, (W, H))

noise_floor = {}
if os.path.exists(f"{OUT_DIR}/phase3_summary.json"):
    with open(f"{OUT_DIR}/phase3_summary.json") as f:
        nf = json.load(f)
        noise_floor = {
            "tile_sigma_cm": nf.get("tile_sigma_median_cm", 0),
            "threshold_cm": nf.get("threshold_used_cm", 0),
        }

for i in range(1, N_FRAMES + 1):
    frame = cv2.imread(f"{FRAMES_DIR}/f_{i:04d}.jpg")
    if frame is None:
        continue

    mask = cv2.imread(f"{MASKS_DIR}/f_{i:04d}.png", 0)
    if mask is not None:
        overlay = frame.copy()
        overlay[mask > 127] = (overlay[mask > 127] * 0.6 + np.array([0, 80, 0]) * 0.4).astype(np.uint8)
        cv2.addWeighted(overlay, 0.7, frame, 0.3, 0, frame)

    for defect in defects:
        cx, cy = 0, 0
        centroid = defect.get("centroid_px", "")
        if isinstance(centroid, str):
            parts = centroid.replace("[", "").replace("]", "").split()
            if len(parts) >= 2:
                cx, cy = float(parts[0]), float(parts[1])
        elif isinstance(centroid, list):
            cx, cy = float(centroid[0]), float(centroid[1])

        first_f = int(defect.get("first_frame", 0))
        dur = int(defect.get("duration_frames", 0))
        if first_f <= i <= first_f + dur:
            cv2.circle(frame, (int(cx), int(cy)), 15, (0, 0, 255), 2)
            cv2.putText(frame, f"{defect.get('peak_dev_cm', '?')}cm",
                        (int(cx) - 30, int(cy) - 20),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)

    t_sec = (i - 1) / FPS
    hud_lines = [
        f"Frame {i}/{N_FRAMES} | t={t_sec:.1f}s",
    ]
    if noise_floor:
        hud_lines.append(f"Sigma={noise_floor.get('tile_sigma_cm', 0):.1f}cm Thresh={noise_floor.get('threshold_cm', 0):.1f}cm")
    hud_lines.append(f"Defects confirmed: {len(defects)}")

    y0 = 30
    for line in hud_lines:
        cv2.putText(frame, line, (15, y0),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 2)
        cv2.putText(frame, line, (15, y0),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.65, (0, 200, 0), 1)
        y0 += 28

    writer.write(frame)

writer.release()
print(f"Phase 4 render complete: {out_path}")
print(f"  {N_FRAMES} frames rendered, {len(defects)} defect overlays")