kopia lustrzana https://github.com/OpenDroneMap/WebODM
Adds support for automatically selecting the proper band filter
Piero Toffanin
rodzic
474e2d844b
commit
530720b699
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@ -156,6 +156,8 @@ camera_filters = [
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'BGRNReL',
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'BGRReNL',
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'RGBNRePL',
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'L', # FLIR camera has a single LWIR band
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# more?
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@ -171,7 +173,7 @@ def lookup_formula(algo, band_order = 'RGB'):
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if algo not in algos:
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raise ValueError("Cannot find algorithm " + algo)
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input_bands = tuple(b for b in re.split(r"([A-Z][a-z]*)", band_order) if b != "")
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def repl(matches):
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@ -193,7 +195,7 @@ def get_algorithm_list(max_bands=3):
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if k.startswith("_"):
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continue
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cam_filters = get_camera_filters_for(algos[k], max_bands)
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cam_filters = get_camera_filters_for(algos[k]['expr'], max_bands)
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if len(cam_filters) == 0:
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continue
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@ -206,9 +208,9 @@ def get_algorithm_list(max_bands=3):
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return res
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def get_camera_filters_for(algo, max_bands=3):
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@lru_cache(maxsize=100)
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def get_camera_filters_for(expr, max_bands=3):
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result = []
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expr = algo['expr']
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pattern = re.compile("([A-Z]+?[a-z]*)")
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bands = list(set(re.findall(pattern, expr)))
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for f in camera_filters:
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@ -226,3 +228,45 @@ def get_camera_filters_for(algo, max_bands=3):
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return result
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@lru_cache(maxsize=1)
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def get_bands_lookup():
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bands_aliases = {
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'R': ['red', 'r'],
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'G': ['green', 'g'],
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'B': ['blue', 'b'],
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'N': ['nir', 'n'],
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'Re': ['rededge', 're'],
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'P': ['panchro', 'p'],
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'L': ['lwir', 'l']
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}
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bands_lookup = {}
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for band in bands_aliases:
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for a in bands_aliases[band]:
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bands_lookup[a] = band
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return bands_lookup
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def get_auto_bands(orthophoto_bands, formula):
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algo = algos.get(formula)
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if not algo:
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raise ValueError("Cannot find formula: " + formula)
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max_bands = len(orthophoto_bands) - 1 # minus alpha
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filters = get_camera_filters_for(algo['expr'], max_bands)
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if not filters:
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raise valueError(f"Cannot find filters for {algo} with max bands {max_bands}")
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bands_lookup = get_bands_lookup()
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band_order = ""
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for band in orthophoto_bands:
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if band['name'] == 'alpha' or (not band['description']):
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continue
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f_band = bands_lookup.get(band['description'].lower())
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if f_band is not None:
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band_order += f_band
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if band_order in filters:
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return band_order, True
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else:
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return filters[0], False # Fallback
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@ -23,7 +23,7 @@ from .custom_colormaps_helper import custom_colormaps
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from app.raster_utils import extension_for_export_format, ZOOM_EXTRA_LEVELS
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from .hsvblend import hsv_blend
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from .hillshade import LightSource
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from .formulas import lookup_formula, get_algorithm_list
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from .formulas import lookup_formula, get_algorithm_list, get_auto_bands
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from .tasks import TaskNestedView
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from rest_framework import exceptions
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from rest_framework.response import Response
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@ -141,6 +141,12 @@ class Metadata(TaskNestedView):
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if boundaries_feature == '': boundaries_feature = None
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if boundaries_feature is not None:
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boundaries_feature = json.loads(boundaries_feature)
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is_auto_bands_match = False
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is_auto_bands = False
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if bands == 'auto' and formula:
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is_auto_bands = True
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bands, is_auto_bands_match = get_auto_bands(task.orthophoto_bands, formula)
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try:
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expr, hrange = lookup_formula(formula, bands)
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if defined_range is not None:
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@ -224,6 +230,8 @@ class Metadata(TaskNestedView):
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colormaps = []
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algorithms = []
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auto_bands = {'filter': '', 'match': None}
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if tile_type in ['dsm', 'dtm']:
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colormaps = ['viridis', 'jet', 'terrain', 'gist_earth', 'pastel1']
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elif formula and bands:
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@ -231,9 +239,14 @@ class Metadata(TaskNestedView):
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'better_discrete_ndvi',
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'viridis', 'plasma', 'inferno', 'magma', 'cividis', 'jet', 'jet_r']
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algorithms = *get_algorithm_list(band_count),
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if is_auto_bands:
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auto_bands['filter'] = bands
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auto_bands['match'] = is_auto_bands_match
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info['color_maps'] = []
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info['algorithms'] = algorithms
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info['auto_bands'] = auto_bands
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if colormaps:
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for cmap in colormaps:
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try:
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@ -254,6 +267,7 @@ class Metadata(TaskNestedView):
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info['maxzoom'] += ZOOM_EXTRA_LEVELS
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info['minzoom'] -= ZOOM_EXTRA_LEVELS
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info['bounds'] = {'value': src.bounds, 'crs': src.dataset.crs}
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return Response(info)
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@ -296,6 +310,8 @@ class Tiles(TaskNestedView):
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if color_map == '': color_map = None
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if hillshade == '' or hillshade == '0': hillshade = None
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if tilesize == '' or tilesize is None: tilesize = 256
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if bands == 'auto' and formula:
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bands, _ = get_auto_bands(task.orthophoto_bands, formula)
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try:
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tilesize = int(tilesize)
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@ -611,4 +627,4 @@ class Export(TaskNestedView):
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else:
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celery_task_id = export_pointcloud.delay(url, epsg=epsg,
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format=export_format).task_id
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return Response({'celery_task_id': celery_task_id, 'filename': filename})
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return Response({'celery_task_id': celery_task_id, 'filename': filename})
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@ -0,0 +1,43 @@
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# Generated by Django 2.2.27 on 2023-10-02 10:21
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import rasterio
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import os
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import django.contrib.postgres.fields.jsonb
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from django.db import migrations
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from webodm import settings
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def update_orthophoto_bands_fields(apps, schema_editor):
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Task = apps.get_model('app', 'Task')
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for t in Task.objects.all():
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bands = []
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orthophoto_path = os.path.join(settings.MEDIA_ROOT, "project", str(t.project.id), "task", str(t.id), "assets", "odm_orthophoto", "odm_orthophoto.tif")
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if os.path.isfile(orthophoto_path):
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try:
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with rasterio.open(orthophoto_path) as f:
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names = [c.name for c in f.colorinterp]
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for i, n in enumerate(names):
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bands.append({
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'name': n,
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'description': f.descriptions[i]
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})
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except Exception as e:
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print(e)
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print("Updating {} (with orthophoto bands: {})".format(t, str(bands)))
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t.orthophoto_bands = bands
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t.save()
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class Migration(migrations.Migration):
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dependencies = [
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('app', '0038_remove_task_console_output'),
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]
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operations = [
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migrations.RunPython(update_orthophoto_bands_fields),
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]
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@ -1024,7 +1024,12 @@ class Task(models.Model):
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if os.path.isfile(orthophoto_path):
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with rasterio.open(orthophoto_path) as f:
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bands = [c.name for c in f.colorinterp]
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names = [c.name for c in f.colorinterp]
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for i, n in enumerate(names):
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bands.append({
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'name': n,
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'description': f.descriptions[i]
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})
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self.orthophoto_bands = bands
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if commit: self.save()
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@ -134,7 +134,7 @@ export default class LayersControlLayer extends React.Component {
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// Check if bands need to be switched
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const algo = this.getAlgorithm(e.target.value);
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if (algo && algo['filters'].indexOf(bands) === -1) bands = algo['filters'][0]; // Pick first
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if (algo && algo['filters'].indexOf(bands) === -1 && bands !== "auto") bands = algo['filters'][0]; // Pick first
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this.setState({formula: e.target.value, bands});
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}
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@ -262,7 +262,7 @@ export default class LayersControlLayer extends React.Component {
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render(){
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const { colorMap, bands, hillshade, formula, histogramLoading, exportLoading } = this.state;
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const { meta, tmeta } = this;
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const { color_maps, algorithms } = tmeta;
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const { color_maps, algorithms, auto_bands } = tmeta;
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const algo = this.getAlgorithm(formula);
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let cmapValues = null;
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@ -298,13 +298,17 @@ export default class LayersControlLayer extends React.Component {
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{bands !== "" && algo ?
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<div className="row form-group form-inline">
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<label className="col-sm-3 control-label">{_("Filter:")}</label>
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<label className="col-sm-3 control-label">{_("Bands:")}</label>
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<div className="col-sm-9 ">
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{histogramLoading ?
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<i className="fa fa-circle-notch fa-spin fa-fw" /> :
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<select className="form-control" value={bands} onChange={this.handleSelectBands}>
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[<select className="form-control" value={bands} onChange={this.handleSelectBands} title={auto_bands.filter !== "" && bands == "auto" ? auto_bands.filter : ""}>
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<option key="auto" value="auto">{_("Automatic")}</option>
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{algo.filters.map(f => <option key={f} value={f}>{f}</option>)}
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</select>}
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</select>,
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bands == "auto" && !auto_bands.match ?
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<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>
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: ""]}
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</div>
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</div> : ""}
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@ -94,6 +94,16 @@ class Map extends React.Component {
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return "";
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}
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hasBands = (bands, orthophoto_bands) => {
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if (!orthophoto_bands) return false;
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console.log(orthophoto_bands)
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for (let i = 0; i < bands.length; i++){
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if (orthophoto_bands.find(b => b.description !== null && b.description.toLowerCase() === bands[i].toLowerCase()) === undefined) return false;
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}
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return true;
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}
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loadImageryLayers(forceAddLayers = false){
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// Cancel previous requests
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if (this.tileJsonRequests) {
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@ -131,7 +141,11 @@ class Map extends React.Component {
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// Single band, probably thermal dataset, in any case we can't render NDVI
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// because it requires 3 bands
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metaUrl += "?formula=Celsius&bands=L&color_map=magma";
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}else if (meta.task && meta.task.orthophoto_bands){
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let formula = this.hasBands(["red", "green", "nir"], meta.task.orthophoto_bands) ? "NDVI" : "VARI";
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metaUrl += `?formula=${formula}&bands=auto&color_map=rdylgn`;
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}else{
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// This should never happen?
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metaUrl += "?formula=NDVI&bands=RGN&color_map=rdylgn";
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}
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}else if (type == "dsm" || type == "dtm"){
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@ -679,7 +679,7 @@ class TestApiTask(BootTransactionTestCase):
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for k in algos:
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a = algos[k]
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filters = get_camera_filters_for(a)
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filters = get_camera_filters_for(a['expr'])
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for f in filters:
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params.append(("orthophoto", "formula={}&bands={}&color_map=rdylgn".format(k, f), status.HTTP_200_OK))
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@ -38,7 +38,7 @@ class TestFormulas(TestCase):
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bands = list(set(re.findall(pattern, f)))
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self.assertTrue(len(bands) <= 3)
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self.assertTrue(get_camera_filters_for(algos['VARI']) == ['RGB'])
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self.assertTrue(get_camera_filters_for(algos['VARI']['expr']) == ['RGB'])
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# Request algorithms with more band filters
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al = get_algorithm_list(max_bands=5)
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2
locale
2
locale
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@ -1 +1 @@
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Subproject commit d253dd5770c42a0705d0f861db3314b08f230a68
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Subproject commit 0a68f6ed5172a8838571a9872bcc3cb4f310794c
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