colmap_matcher.sh

#!/bin/bash
echo ""
echo "Executing colmap_matcher.sh ..."

sequence_path="$1"
exp_folder="$2" 
exp_id="$3" 
settings_yaml="$4"
calibration_yaml="$5"
rgb_csv="$6"
matcher_type="$7"
use_gpu="$8"
camera_name="$9"
matching_type="${10}"

exp_folder_colmap="${exp_folder}/colmap_${exp_id}"
rgb_dir=$(awk -F, 'NR==2 { split($2,a,"/"); print a[1]; exit }' "$rgb_csv")
rgb_path="${sequence_path}/${rgb_dir}"

# matching_type: FeatureExtraction.type + FeatureMatching.type
feature_matching_type=""
feature_extraction_type="SIFT"

case "${matching_type}" in
    sift_bruteforce)
        feature_extraction_type="SIFT"
        feature_matching_type="SIFT_BRUTEFORCE"
        ;;
    sift_lightglue)
        feature_extraction_type="SIFT"
        feature_matching_type="SIFT_LIGHTGLUE"
        ;;
    aliked_bruteforce)
        feature_extraction_type="ALIKED_N16ROT"
        feature_matching_type="ALIKED_BRUTEFORCE"
        ;;
    aliked_lightglue)
        feature_extraction_type="ALIKED_N16ROT"
        feature_matching_type="ALIKED_LIGHTGLUE"
        ;;
    *)
        echo "Unknown matching_type: ${matching_type}"
        exit 1
        ;;
esac

# Get calibration model
read -r calibration_model more_ <<< $(python3 Baselines/colmap/get_calibration.py "$calibration_yaml" "$camera_name")

# Create colmap image list
colmap_image_list="${exp_folder_colmap}/colmap_image_list.txt"
python3 Baselines/colmap/create_colmap_image_list.py "$rgb_csv" "$colmap_image_list" "$camera_name"

# Create Colmap Database
database="${exp_folder_colmap}/colmap_database.db"
rm -rf ${database}
colmap database_creator --database_path ${database} 

# Feature extractor
echo "    colmap feature_extractor (${feature_extraction_type}) ..."

if [ "${calibration_model}" == "unknown" ]
then
    echo "        camera model : $calibration_model"
    colmap feature_extractor \
       --database_path ${database} \
       --image_path ${rgb_path} \
       --image_list_path ${colmap_image_list} \
       --ImageReader.camera_model OPENCV \
       --ImageReader.single_camera 1 \
       --ImageReader.single_camera_per_folder 1 \
       --FeatureExtraction.type ${feature_extraction_type} \
       --FeatureExtraction.use_gpu ${use_gpu}
fi

if [ "${calibration_model}" == "pinhole" ]
then
    read -r calibration_model fx fy cx cy <<< $(python3 Baselines/colmap/get_calibration.py "$calibration_yaml" "$camera_name")
    echo "        camera model : $calibration_model"
    echo "            fx: $fx , fy: $fy , cx: $cx , cy: $cy"
    colmap feature_extractor \
        --database_path ${database} \
        --image_path ${rgb_path} \
        --image_list_path ${colmap_image_list} \
        --ImageReader.camera_model PINHOLE \
        --ImageReader.single_camera 1 \
        --ImageReader.single_camera_per_folder 1 \
        --FeatureExtraction.type ${feature_extraction_type} \
        --FeatureExtraction.use_gpu ${use_gpu} \
        --ImageReader.camera_params "${fx},${fy},${cx},${cy}"
fi

if [ "${calibration_model}" == "radtan4" ]
then
    read -r calibration_model fx fy cx cy k1 k2 p1 p2 <<< $(python3 Baselines/colmap/get_calibration.py "$calibration_yaml" "$camera_name")
    echo "        camera model : $calibration_model"
    echo "            fx: $fx , fy: $fy , cx: $cx , cy: $cy"
    echo "            k1: $k1 , k2: $k2 , p1: $p1 , p2: $p2"
    colmap feature_extractor \
        --database_path ${database} \
        --image_path ${rgb_path} \
        --image_list_path ${colmap_image_list} \
        --ImageReader.camera_model "OPENCV" \
        --ImageReader.single_camera 1 \
        --ImageReader.single_camera_per_folder 1 \
        --FeatureExtraction.type ${feature_extraction_type} \
        --FeatureExtraction.use_gpu ${use_gpu} \
        --ImageReader.camera_params "${fx},${fy},${cx},${cy},${k1},${k2},${p1},${p2}"
fi

if [ "${calibration_model}" == "radtan5" ]
then
    read -r calibration_model fx fy cx cy k1 k2 p1 p2 k3 <<< $(python3 Baselines/colmap/get_calibration.py "$calibration_yaml" "$camera_name")
    echo "        camera model : $calibration_model"
    echo "            fx: $fx , fy: $fy , cx: $cx , cy: $cy"
    echo "            k1: $k1 , k2: $k2 , p1: $p1 , p2: $p2, k3: $k3"
    colmap feature_extractor \
        --database_path ${database} \
        --image_path ${rgb_path} \
        --image_list_path ${colmap_image_list} \
        --ImageReader.camera_model "FULL_OPENCV" \
        --ImageReader.single_camera 1 \
        --ImageReader.single_camera_per_folder 1 \
        --FeatureExtraction.type ${feature_extraction_type} \
        --FeatureExtraction.use_gpu ${use_gpu} \
        --ImageReader.camera_params "${fx},${fy},${cx},${cy},${k1},${k2},${p1},${p2},${k3},0,0,0"
fi

if [ "${calibration_model}" == "equid4" ]
then
    read -r calibration_model fx fy cx cy k1 k2 k3 k4 <<< $(python3 Baselines/colmap/get_calibration.py "$calibration_yaml" "$camera_name")
    echo "        camera model : $calibration_model"
    echo "            fx: $fx , fy: $fy , cx: $cx , cy: $cy"
    echo "            k1: $k1 , k2: $k2 , k3: $k3 , k4: $k4"
    colmap feature_extractor \
        --database_path ${database} \
        --image_path ${rgb_path} \
        --image_list_path ${colmap_image_list} \
        --ImageReader.camera_model "OPENCV_FISHEYE" \
        --ImageReader.single_camera 1 \
        --ImageReader.single_camera_per_folder 1 \
        --FeatureExtraction.type ${feature_extraction_type} \
        --FeatureExtraction.use_gpu ${use_gpu} \
        --ImageReader.camera_params "${fx},${fy},${cx},${cy},${k1},${k2},${k3},${k4}"
fi

# Exhaustive Feature Matcher
if [ "${matcher_type}" == "exhaustive" ]; 
then
  echo "    colmap exhaustive_matcher (${feature_matching_type}) ..."
  colmap exhaustive_matcher \
    --database_path "${database}" \
    --FeatureMatching.type "${feature_matching_type}" \
    --FeatureMatching.use_gpu "${use_gpu}"
fi

# Sequential Feature Matcher
if [ "${matcher_type}" == "sequential" ]
then
  num_rgb=$(( $(wc -l < "$rgb_csv") - 1 ))

  # Pick vocabulary tree based on the number of images
  vocabulary_tree="Baselines/colmap/vocab_tree_flickr100K_words32K.bin"
  if [ "$num_rgb" -gt 1000 ]; then
    vocabulary_tree="Baselines/colmap/vocab_tree_flickr100K_words256K.bin"
  fi
  if [ "$num_rgb" -gt 10000 ]; then
    vocabulary_tree="Baselines/colmap/vocab_tree_flickr100K_words1M.bin"
  fi

  echo "    colmap sequential_matcher (${feature_matching_type}) ..."
  echo "        Vocabulary Tree: $vocabulary_tree"
  colmap sequential_matcher \
    --database_path "${database}" \
    --SequentialMatching.loop_detection 1 \
    --SequentialMatching.vocab_tree_path ${vocabulary_tree} \
    --FeatureMatching.type "${feature_matching_type}" \
    --FeatureMatching.use_gpu "${use_gpu}"
fi