feat: auto-generate metadata markdown for each panorama

Includes: coverage, FOV, camera specs, photogrammetry reference,
equirectangular projection info, timing, image list.

Also: docker-compose user fix (1000:100) to avoid root-owned files.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

pipeline/panorama_metadata.py

@@ -0,0 +1,218 @@
+#!/usr/bin/env python3
+"""
+Generate metadata markdown file for a completed panorama.
+Can be called standalone or imported by the pipeline.
+"""
+
+import json
+import math
+import os
+import re
+import sys
+from datetime import datetime
+
+
+def generate_metadata(work_dir, output_name, sol, camera, rover,
+                      azs, els, img_w, img_h, fov, n_cps, timings,
+                      original_images, blender, output_png):
+    """Generate a metadata .md file for a completed panorama."""
+
+    md_path = os.path.join(work_dir, f"{output_name}_metadata.md")
+
+    # Image info
+    n_images = len(azs)
+    az_min = min(azs)
+    az_max = max(azs)
+    az_range = az_max - az_min
+    el_min = min(els)
+    el_max = max(els)
+    el_range = el_max - el_min
+
+    # Output image info
+    out_w, out_h, out_size_mb = 0, 0, 0
+    if output_png and os.path.exists(output_png):
+        out_size_mb = os.path.getsize(output_png) / 1024 / 1024
+        try:
+            from PIL import Image
+            Image.MAX_IMAGE_PIXELS = None
+            img = Image.open(output_png)
+            out_w, out_h = img.size
+        except Exception:
+            pass
+
+    # Gaps analysis
+    sorted_azs = sorted(azs)
+    gaps = [sorted_azs[i+1] - sorted_azs[i] for i in range(len(sorted_azs)-1)]
+    avg_gap = sum(gaps) / len(gaps) if gaps else 0
+    max_gap = max(gaps) if gaps else 0
+    min_gap = min(gaps) if gaps else 0
+
+    # Overlap estimate
+    overlap_per_pair = fov - avg_gap if fov > avg_gap else 0
+
+    # Coverage estimate
+    total_coverage_h = az_range + fov  # first and last image extend beyond their centers
+    coverage_pct = min(total_coverage_h / 360 * 100, 100)
+
+    # Vertical coverage
+    total_coverage_v = el_range + (img_h / img_w * fov)  # approximate VFOV
+    vfov_per_image = img_h / img_w * fov  # approximate
+
+    # Resolution estimate (degrees per pixel in output)
+    if out_w > 0:
+        deg_per_px_h = total_coverage_h / out_w
+        px_per_deg_h = out_w / total_coverage_h
+    else:
+        deg_per_px_h = 0
+        px_per_deg_h = 0
+
+    # Equirectangular full sphere equivalent
+    equiv_360_w = int(px_per_deg_h * 360) if px_per_deg_h > 0 else 0
+    equiv_180_h = int(px_per_deg_h * 180) if px_per_deg_h > 0 else 0
+
+    # Image list with details
+    image_details = []
+    for i, (az, el) in enumerate(zip(azs, els)):
+        fname = os.path.basename(original_images[i]) if i < len(original_images) else f"image_{i}"
+        image_details.append((i, fname, az, el))
+
+    total_time = sum(timings.values()) if timings else 0
+
+    content = f"""# Panorama Metadata — Sol {sol}
+
+> Auto-generated by mars-panorama-pipeline on {datetime.utcnow().strftime('%Y-%m-%d %H:%M UTC')}
+
+---
+
+## Summary
+
+| Property | Value |
+|----------|-------|
+| **Sol** | {sol} |
+| **Rover** | {rover.capitalize()} |
+| **Camera** | {camera} |
+| **Images** | {n_images} |
+| **Control Points** | {n_cps:,} |
+| **Blender** | {blender} |
+| **Processing Time** | {total_time:.0f}s ({total_time/60:.1f} min) |
+| **Output** | {out_w} x {out_h} pixels |
+| **File Size** | {out_size_mb:.1f} MB |
+
+---
+
+## Coverage
+
+| Property | Value |
+|----------|-------|
+| **Azimuth Range** | {az_min:.1f}° to {az_max:.1f}° ({az_range:.1f}° span) |
+| **Elevation Range** | {el_min:.1f}° to {el_max:.1f}° ({el_range:.1f}° span) |
+| **Horizontal Coverage** | ~{total_coverage_h:.0f}° ({coverage_pct:.0f}% of 360°) |
+| **Vertical Coverage** | ~{total_coverage_v:.0f}° |
+| **FOV per Image** | {fov:.2f}° (horizontal) |
+| **Avg Gap Between Images** | {avg_gap:.1f}° |
+| **Avg Overlap** | {overlap_per_pair:.1f}° per pair |
+
+### Equirectangular Projection Info
+
+| Property | Value |
+|----------|-------|
+| **Projection** | Equirectangular (Hugin f2) |
+| **Resolution** | {px_per_deg_h:.1f} px/deg |
+| **Full 360° Equivalent Width** | {equiv_360_w} px |
+| **Full 180° Equivalent Height** | {equiv_180_h} px |
+| **Suitable for VR Skybox** | {'Yes' if coverage_pct > 80 else 'Partial — needs gap filling'} |
+
+---
+
+## Camera Specifications
+
+| Property | Value |
+|----------|-------|
+| **Camera** | {camera} |
+| **Image Size (per frame)** | {img_w} x {img_h} px |
+| **HFOV** | {fov:.2f}° |
+| **VFOV** | ~{vfov_per_image:.1f}° (estimated) |
+"""
+
+    if "NAVCAM" in camera:
+        content += f"""| **Tile Combining** | Yes (01+04, 16px overlap) |
+| **Native Sensor** | 5120 x 3840 (20 MP) |
+| **Focal Length** | 19.1 mm, f/12 |
+| **Empirical f (pixels)** | 1468 px |
+"""
+    elif "MCZ" in camera:
+        content += f"""| **Tile Combining** | No (single frame) |
+| **Native Sensor** | 1648 x 1200 |
+| **Focal Length** | 26-110 mm (zoom) |
+| **Zoom Used** | Wide (26 mm) based on FOV |
+"""
+
+    content += f"""
+---
+
+## Photogrammetry Reference
+
+These parameters are needed for photogrammetric reconstruction of the terrain.
+
+| Property | Value |
+|----------|-------|
+| **Number of Viewpoints** | {n_images} |
+| **Baseline Between Views** | ~{avg_gap:.1f}° azimuth ({avg_gap * 0.017:.3f} rad) |
+| **Stereo Pair Available** | {'Yes (Left+Right NavCam)' if 'NAVCAM' in camera else 'Single camera only'} |
+| **Depth Estimation Potential** | {'Good — multiple overlapping views' if overlap_per_pair > 5 else 'Limited — minimal overlap'} |
+| **Recommended Software** | Meshroom, COLMAP, OpenMVS |
+| **Notes** | Images sorted by azimuth. Adjacent images have ~{overlap_per_pair:.0f}° overlap. |
+
+### Rover Position (for scene reconstruction)
+
+The rover is at the center of the panorama. All azimuth/elevation values are
+relative to the rover's mast coordinate system.
+
+- **Mast height**: ~2.2m above ground (Perseverance)
+- **Azimuth 0°**: Rover forward direction
+- **Elevation 0°**: Horizontal plane
+- **Negative elevation**: Below horizon (ground)
+
+---
+
+## Timing Breakdown
+
+| Step | Time |
+|------|------|
+"""
+    for step, t in timings.items():
+        content += f"| {step} | {t:.1f}s |\n"
+    content += f"| **Total** | **{total_time:.0f}s** |\n"
+
+    content += f"""
+---
+
+## Image List
+
+| # | Azimuth | Elevation | Filename |
+|---|---------|-----------|----------|
+"""
+    for i, fname, az, el in image_details:
+        content += f"| {i} | {az:.1f}° | {el:.1f}° | {fname} |\n"
+
+    content += f"""
+---
+
+## Pipeline Parameters
+
+```
+Camera FOV: {fov:.2f}°
+Image size: {img_w} x {img_h}
+Blender: {blender}
+Projection: equirectangular (f2)
+Photometric optimization: disabled (geometry only)
+CLAHE: clipLimit=2.0, tileGrid=16x16
+Vignette correction: 0.35 strength
+```
+"""
+
+    with open(md_path, 'w') as f:
+        f.write(content)
+
+    print(f"  Metadata: {md_path}")
+    return md_path

pipeline/panorama_pipeline.py

@@ -19,6 +19,7 @@ import cv2
 import glob
 import math
 import mysql.connector
+from panorama_metadata import generate_metadata
 import numpy as np
 import os
 import re
@@ -515,6 +516,19 @@ def run_pipeline(work_dir, clahe_images, original_images, azs, els,
     if os.path.exists(out_tif):
         os.remove(out_tif)
 
+    # Generate metadata file
+    try:
+        generate_metadata(
+            work_dir=work_dir, output_name=output_name,
+            sol=int(re.search(r'\d+', output_name).group()),
+            camera=camera or "unknown", rover="perseverance",
+            azs=azs, els=els, img_w=img_w, img_h=img_h, fov=fov,
+            n_cps=len(cp_lines), timings=timings,
+            original_images=original_images, blender=blender,
+            output_png=out_png)
+    except Exception as e:
+        print(f"  Warning: metadata generation failed: {e}")
+
     return out_png, timings