AutoTracker workflow using GLOMAP

readme-mac.md

Automated Video to 3D Scan Workflow (GLOMAP + COLMAP) for macOS

This repository contains a Bash script for automating a photogrammetry workflow on macOS using GLOMAP and COLMAP. It takes video files as input, extracts frames via FFmpeg, and generates a 3D sparse point cloud for each video.

This script is a macOS/Apple Silicon adaptation of Polyfjord’s workflow, rewritten to run smoothly on Mac systems.

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Features

• One-Command Automation: Processes all videos in the input folder in a single run.
• CPU & Apple Silicon Ready: Automatically detects CPU threads and works on M-series Macs.
• Error Handling: Skips already processed videos and ensures the workflow executes step by step without breaking.
• Organized Output: Keeps results clean with a structured project folder.
• COLMAP + GLOMAP Integration: Extracts features, performs sequential matching, and runs sparse reconstruction automatically.
• TXT Export: Converts COLMAP models to TXT format for easier inspection or import.

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Requirements

Software

• COLMAP – Structure-from-motion and multi-view stereo pipeline.
• GLOMAP – COLMAP extension for automated mapping.
• FFmpeg – For frame extraction.

Recommended Installation Method:

• Colmap and Glomap:

Install by following this guide

• FFmpeg:

brew install ffmpeg

Folder Structure

    Project_Folder/
    ├── VIDEOS/      # Place input video files (.mp4, .mov) here.
    ├── SCENES/      # The script saves all outputs here.
    └── SCRIPTS/     # The run_glomap.sh script lives here.

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How to Use

1. Set Up Folders: Create the structure shown above.

2. Add Videos: Copy your .mp4 or .mov files into the VIDEOS/ folder.

3. Save the Script: Place the script (run_glomap.sh) in the SCRIPTS/ folder.

4. Update Paths: Edit the script and update these variables to match your system installation:

   FFMPEG="/opt/homebrew/bin/ffmpeg"
   COLMAP="/usr/local/bin/colmap"
   GLOMAP="/usr/local/bin/glomap"

   If you are unsure of the paths, run:

   which colmap ffmpeg glomap

5. Make it Executable:

   chmod +x run_glomap.sh

6. Run the Script: From inside the SCRIPTS/ folder:

   ./run_glomap.sh

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Troubleshooting

• COLMAP/GLOMAP/FFmpeg not found: Ensure the paths in the script match your system installation.

• No frames extracted: Check that your video files are valid and playable by FFmpeg.

• Slow processing: Reduce --SiftExtraction.max_image_size (e.g., from 4096 → 2048) or process shorter clips.

• GPU/CPU issues: This script primarily uses CPU. M-series Macs may benefit from COLMAP GPU support if configured.

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Conclusion

This script fully automates Polyfjord’s photogrammetry workflow on macOS using GLOMAP and COLMAP, making it easy to generate 3D sparse point clouds from videos. Future updates may include optimizations and support for additional Mac hardware.

run_glomap.sh

#!/bin/bash
# ================================================================
#  BASH SCRIPT FOR AUTOMATED PHOTOGRAMMETRY TRACKING WORKFLOW (GLOMAP + COLMAP)
#  macOS / Apple Silicon version (Could work in Intel Mac - Not tested yet)
# ================================================================

set -e  # Stop on error

# --- Resolve top-level folder (one up from this script) ---
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
TOP="$(dirname "$SCRIPT_DIR")"

# --- Key paths ---
VIDEOS_DIR="$TOP/VIDEOS"
SCENES_DIR="$TOP/SCENES"

# --- System-wide executables ---
FFMPEG="/opt/homebrew/bin/ffmpeg"
COLMAP="/usr/local/bin/colmap"
GLOMAP="/usr/local/bin/glomap"

# --- CPU thread count ---
NUM_THREADS=$(sysctl -n hw.ncpu)

# --- Ensure executables exist ---
for cmd in "$FFMPEG" "$COLMAP" "$GLOMAP"; do
    if [ ! -x "$cmd" ]; then
        echo "[ERROR] Executable not found: $cmd" >&2
        exit 1
    fi
done

# --- Ensure required folders exist ---
if [ ! -d "$VIDEOS_DIR" ]; then
    echo "[ERROR] Input folder '$VIDEOS_DIR' missing." >&2
    exit 1
fi
mkdir -p "$SCENES_DIR"

# --- Count videos ---
TOTAL=$(find "$VIDEOS_DIR" -maxdepth 1 -type f | wc -l | tr -d ' ')
if [ "$TOTAL" -eq 0 ]; then
    echo "[INFO] No video files found in '$VIDEOS_DIR'."
    exit 0
fi

echo "=============================================================="
echo " Starting GLOMAP pipeline on $TOTAL video(s) …"
echo "=============================================================="

IDX=0
for VIDEO_FILE in "$VIDEOS_DIR"/*; do
    [ -f "$VIDEO_FILE" ] || continue
    IDX=$((IDX + 1))
    BASENAME=$(basename "$VIDEO_FILE")
    BASE="${BASENAME%.*}"

    echo
    echo "[$IDX/$TOTAL] === Processing \"$BASENAME\" ==="

    SCENE_DIR="$SCENES_DIR/$BASE"
    IMG_DIR="$SCENE_DIR/images"
    SPARSE_DIR="$SCENE_DIR/sparse"

    # Skip if already reconstructed
    if [ -d "$SCENE_DIR" ]; then
        echo "       • Skipping \"$BASE\" – already reconstructed."
        continue
    fi

    # Create directories
    mkdir -p "$IMG_DIR" "$SPARSE_DIR"

    # --- 1) Extract frames ---
    echo "       [1/4] Extracting frames …"
    "$FFMPEG" -loglevel error -stats -i "$VIDEO_FILE" -qscale:v 2 "$IMG_DIR/frame_%06d.jpg"

    # Remove dot-underscore macOS files
    find "$IMG_DIR" -name '._*' -delete

    if ! ls "$IMG_DIR"/*.jpg &> /dev/null; then
        echo "       × No frames extracted – skipping \"$BASE\"."
        rm -rf "$SCENE_DIR"
        continue
    fi

    # --- 2) Feature extraction (COLMAP) ---
    echo "       [2/4] COLMAP feature_extractor …"
    "$COLMAP" feature_extractor \
        --database_path "$SCENE_DIR/database.db" \
        --image_path "$IMG_DIR" \
        --ImageReader.single_camera 1 \
        --SiftExtraction.max_image_size 4096

    # --- 3) Sequential matching (COLMAP) ---
    echo "       [3/4] COLMAP sequential_matcher …"
    "$COLMAP" sequential_matcher \
        --database_path "$SCENE_DIR/database.db" \
        --SequentialMatching.overlap 15

    # --- 4) Sparse reconstruction (GLOMAP) ---
    echo "       [4/4] GLOMAP mapper …"
    "$GLOMAP" mapper \
        --database_path "$SCENE_DIR/database.db" \
        --image_path "$IMG_DIR" \
        --output_path "$SPARSE_DIR"

    # --- Export TXT inside model folder ---
    if [ -d "$SPARSE_DIR/0" ]; then
        "$COLMAP" model_converter \
            --input_path "$SPARSE_DIR/0" \
            --output_path "$SPARSE_DIR/0" \
            --output_type TXT > /dev/null
        "$COLMAP" model_converter \
            --input_path "$SPARSE_DIR/0" \
            --output_path "$SPARSE_DIR" \
            --output_type TXT > /dev/null
    fi

    echo "       ✓ Finished \"$BASE\"  ($IDX/$TOTAL)"
done

echo "--------------------------------------------------------------"
echo " All jobs finished – results are in \"$SCENES_DIR\"."
echo "--------------------------------------------------------------"

Amazing work, it took very little adaptation to work for Linux and I have credited you in my fork https://gist.github.com/Norgus/9e877924949d778db12c534ff1bafe36