Adds support for automatically selecting the proper band filter

app/api/formulas.py

@@ -156,6 +156,8 @@
     'BGRNReL',
     'BGRReNL',
 
+    'RGBNRePL',
+
     'L', # FLIR camera has a single LWIR band
 
     # more?
@@ -171,7 +173,7 @@ def lookup_formula(algo, band_order = 'RGB'):
 
     if algo not in algos:
         raise ValueError("Cannot find algorithm " + algo)
-
+    
     input_bands = tuple(b for b in re.split(r"([A-Z][a-z]*)", band_order) if b != "")
 
     def repl(matches):
@@ -193,7 +195,7 @@ def get_algorithm_list(max_bands=3):
         if k.startswith("_"):
             continue
 
-        cam_filters = get_camera_filters_for(algos[k], max_bands)
+        cam_filters = get_camera_filters_for(algos[k]['expr'], max_bands)
 
         if len(cam_filters) == 0:
             continue
@@ -206,9 +208,9 @@ def get_algorithm_list(max_bands=3):
 
     return res
 
-def get_camera_filters_for(algo, max_bands=3):
+@lru_cache(maxsize=100)
+def get_camera_filters_for(expr, max_bands=3):
     result = []
-    expr = algo['expr']
     pattern = re.compile("([A-Z]+?[a-z]*)")
     bands = list(set(re.findall(pattern, expr)))
     for f in camera_filters:
@@ -226,3 +228,45 @@ def get_camera_filters_for(algo, max_bands=3):
 
     return result
 
+@lru_cache(maxsize=1)
+def get_bands_lookup():
+    bands_aliases = {
+        'R': ['red', 'r'],
+        'G': ['green', 'g'],
+        'B': ['blue', 'b'],
+        'N': ['nir', 'n'],
+        'Re': ['rededge', 're'],
+        'P': ['panchro', 'p'],
+        'L': ['lwir', 'l']
+    }
+    bands_lookup = {}
+    for band in bands_aliases:
+        for a in bands_aliases[band]:
+            bands_lookup[a] = band
+    return bands_lookup
+
+def get_auto_bands(orthophoto_bands, formula):
+    algo = algos.get(formula)
+    if not algo:
+        raise ValueError("Cannot find formula: " + formula)
+
+    max_bands = len(orthophoto_bands) - 1 # minus alpha
+    filters = get_camera_filters_for(algo['expr'], max_bands)
+    if not filters:
+        raise valueError(f"Cannot find filters for {algo} with max bands {max_bands}")
+
+    bands_lookup = get_bands_lookup()
+    band_order = ""
+
+    for band in orthophoto_bands:
+        if band['name'] == 'alpha' or (not band['description']):
+            continue
+        f_band = bands_lookup.get(band['description'].lower())
+
+        if f_band is not None:
+            band_order += f_band
+
+    if band_order in filters:
+        return band_order, True
+    else:
+        return filters[0], False # Fallback

app/api/tiler.py

@@ -23,7 +23,7 @@
 from app.raster_utils import extension_for_export_format, ZOOM_EXTRA_LEVELS
 from .hsvblend import hsv_blend
 from .hillshade import LightSource
-from .formulas import lookup_formula, get_algorithm_list
+from .formulas import lookup_formula, get_algorithm_list, get_auto_bands
 from .tasks import TaskNestedView
 from rest_framework import exceptions
 from rest_framework.response import Response
@@ -141,6 +141,12 @@ def get(self, request, pk=None, project_pk=None, tile_type=""):
         if boundaries_feature == '': boundaries_feature = None
         if boundaries_feature is not None:
             boundaries_feature = json.loads(boundaries_feature)
+
+        is_auto_bands_match = False
+        is_auto_bands = False
+        if bands == 'auto' and formula:
+            is_auto_bands = True
+            bands, is_auto_bands_match = get_auto_bands(task.orthophoto_bands, formula)
         try:
             expr, hrange = lookup_formula(formula, bands)
             if defined_range is not None:
@@ -224,16 +230,23 @@ def get(self, request, pk=None, project_pk=None, tile_type=""):
 
         colormaps = []
         algorithms = []
+        auto_bands = {'filter': '', 'match': None}
+
         if tile_type in ['dsm', 'dtm']:
             colormaps = ['viridis', 'jet', 'terrain', 'gist_earth', 'pastel1']
         elif formula and bands:
             colormaps = ['rdylgn', 'spectral', 'rdylgn_r', 'spectral_r', 'rplumbo', 'discrete_ndvi',
                          'better_discrete_ndvi',
                          'viridis', 'plasma', 'inferno', 'magma', 'cividis', 'jet', 'jet_r']
             algorithms = *get_algorithm_list(band_count),
+            if is_auto_bands:
+                auto_bands['filter'] = bands
+                auto_bands['match'] = is_auto_bands_match
 
         info['color_maps'] = []
         info['algorithms'] = algorithms
+        info['auto_bands'] = auto_bands
+
         if colormaps:
             for cmap in colormaps:
                 try:
@@ -254,6 +267,7 @@ def get(self, request, pk=None, project_pk=None, tile_type=""):
         info['maxzoom'] += ZOOM_EXTRA_LEVELS
         info['minzoom'] -= ZOOM_EXTRA_LEVELS
         info['bounds'] = {'value': src.bounds, 'crs': src.dataset.crs}
+
         return Response(info)
 
 
@@ -296,6 +310,8 @@ def get(self, request, pk=None, project_pk=None, tile_type="", z="", x="", y="",
         if color_map == '': color_map = None
         if hillshade == '' or hillshade == '0': hillshade = None
         if tilesize == '' or tilesize is None: tilesize = 256
+        if bands == 'auto' and formula:
+            bands, _ = get_auto_bands(task.orthophoto_bands, formula)
 
         try:
             tilesize = int(tilesize)
@@ -611,4 +627,4 @@ def post(self, request, pk=None, project_pk=None, asset_type=None):
             else:
                 celery_task_id = export_pointcloud.delay(url, epsg=epsg, 
                                                             format=export_format).task_id
-                return Response({'celery_task_id': celery_task_id, 'filename': filename})
+                return Response({'celery_task_id': celery_task_id, 'filename': filename})

app/migrations/0039_task_orthophoto_bands.py

@@ -0,0 +1,43 @@
+# Generated by Django 2.2.27 on 2023-10-02 10:21
+
+import rasterio
+import os
+import django.contrib.postgres.fields.jsonb
+from django.db import migrations
+from webodm import settings
+
+def update_orthophoto_bands_fields(apps, schema_editor):
+    Task = apps.get_model('app', 'Task')
+
+    for t in Task.objects.all():
+
+        bands = []
+        orthophoto_path = os.path.join(settings.MEDIA_ROOT, "project", str(t.project.id), "task", str(t.id), "assets", "odm_orthophoto", "odm_orthophoto.tif")
+
+        if os.path.isfile(orthophoto_path):
+            try:
+                with rasterio.open(orthophoto_path) as f:
+                    names = [c.name for c in f.colorinterp]
+                    for i, n in enumerate(names):
+                        bands.append({
+                            'name': n,
+                            'description': f.descriptions[i]
+                        })
+            except Exception as e:
+                print(e)
+
+        print("Updating {} (with orthophoto bands: {})".format(t, str(bands)))
+
+        t.orthophoto_bands = bands
+        t.save()
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('app', '0038_remove_task_console_output'),
+    ]
+
+    operations = [
+        migrations.RunPython(update_orthophoto_bands_fields),
+    ]

app/models/task.py

@@ -1024,7 +1024,12 @@ def update_orthophoto_bands_field(self, commit=False):
 
         if os.path.isfile(orthophoto_path):
             with rasterio.open(orthophoto_path) as f:
-                bands = [c.name for c in f.colorinterp]
+                names = [c.name for c in f.colorinterp]
+                for i, n in enumerate(names):
+                    bands.append({
+                        'name': n,
+                        'description': f.descriptions[i]
+                    })
 
         self.orthophoto_bands = bands
         if commit: self.save()

app/static/app/js/components/LayersControlLayer.jsx

@@ -134,7 +134,7 @@ export default class LayersControlLayer extends React.Component {
 
     // Check if bands need to be switched
     const algo = this.getAlgorithm(e.target.value);
-    if (algo && algo['filters'].indexOf(bands) === -1) bands = algo['filters'][0]; // Pick first
+    if (algo && algo['filters'].indexOf(bands) === -1 && bands !== "auto") bands = algo['filters'][0]; // Pick first
 
     this.setState({formula: e.target.value, bands});
   }
@@ -262,7 +262,7 @@ export default class LayersControlLayer extends React.Component {
   render(){
     const { colorMap, bands, hillshade, formula, histogramLoading, exportLoading } = this.state;
     const { meta, tmeta } = this;
-    const { color_maps, algorithms } = tmeta;
+    const { color_maps, algorithms, auto_bands } = tmeta;
     const algo = this.getAlgorithm(formula);
 
     let cmapValues = null;
@@ -298,13 +298,17 @@ export default class LayersControlLayer extends React.Component {
 
             {bands !== "" && algo ? 
             <div className="row form-group form-inline">
-                <label className="col-sm-3 control-label">{_("Filter:")}</label>
+                <label className="col-sm-3 control-label">{_("Bands:")}</label>
                 <div className="col-sm-9 ">
                     {histogramLoading ? 
                     <i className="fa fa-circle-notch fa-spin fa-fw" /> :
-                    <select className="form-control" value={bands} onChange={this.handleSelectBands}>
+                    [<select className="form-control" value={bands} onChange={this.handleSelectBands} title={auto_bands.filter !== "" && bands == "auto" ? auto_bands.filter : ""}>
+                        <option key="auto" value="auto">{_("Automatic")}</option>
                         {algo.filters.map(f => <option key={f} value={f}>{f}</option>)}
-                    </select>}
+                    </select>,
+                    bands == "auto" && !auto_bands.match ? 
+                    <i style={{marginLeft: '4px'}} title={interpolate(_("Not every band for %(name)s could be automatically identified."), {name: algo.id}) + "\n" + _("Your sensor might not have the proper bands for using this algorithm.")} className="fa fa-exclamation-circle info-button"></i>
+                    : ""]}
                 </div>
             </div> : ""}
 

app/static/app/js/components/Map.jsx

@@ -94,6 +94,16 @@ class Map extends React.Component {
       return "";
   }
 
+  hasBands = (bands, orthophoto_bands) => {
+    if (!orthophoto_bands) return false;
+    console.log(orthophoto_bands)
+    for (let i = 0; i < bands.length; i++){
+      if (orthophoto_bands.find(b => b.description !== null && b.description.toLowerCase() === bands[i].toLowerCase()) === undefined) return false;
+    }
+
+    return true;
+  }
+
   loadImageryLayers(forceAddLayers = false){
     // Cancel previous requests
     if (this.tileJsonRequests) {
@@ -131,7 +141,11 @@ class Map extends React.Component {
             // Single band, probably thermal dataset, in any case we can't render NDVI
             // because it requires 3 bands
             metaUrl += "?formula=Celsius&bands=L&color_map=magma";
+          }else if (meta.task && meta.task.orthophoto_bands){
+            let formula = this.hasBands(["red", "green", "nir"], meta.task.orthophoto_bands) ? "NDVI" : "VARI";
+            metaUrl += `?formula=${formula}&bands=auto&color_map=rdylgn`;
           }else{
+            // This should never happen?
             metaUrl += "?formula=NDVI&bands=RGN&color_map=rdylgn";
           }
         }else if (type == "dsm" || type == "dtm"){

app/tests/test_api_task.py

@@ -679,7 +679,7 @@ def test_task(self):
 
             for k in algos:
                 a = algos[k]
-                filters = get_camera_filters_for(a)
+                filters = get_camera_filters_for(a['expr'])
 
                 for f in filters:
                     params.append(("orthophoto", "formula={}&bands={}&color_map=rdylgn".format(k, f), status.HTTP_200_OK))

app/tests/test_formulas.py

@@ -38,7 +38,7 @@ def test_algo_list(self):
                 bands = list(set(re.findall(pattern, f)))
                 self.assertTrue(len(bands) <= 3)
 
-        self.assertTrue(get_camera_filters_for(algos['VARI']) == ['RGB'])
+        self.assertTrue(get_camera_filters_for(algos['VARI']['expr']) == ['RGB'])
 
         # Request algorithms with more band filters
         al = get_algorithm_list(max_bands=5)