Merge pull request #589 from weecology/warn_on_crs_mismatch

when the CRS of the shapefile and RGB data don't match, don't proceed…

deepforest/main.py

@@ -83,7 +83,6 @@ def __init__(self,
 
         self.create_model()
 
-
         # Metrics
         self.iou_metric = IntersectionOverUnion(
             class_metrics=True, iou_threshold=self.config["validation"]["iou_threshold"])

deepforest/utilities.py

@@ -294,6 +294,11 @@ def shapefile_to_annotations(shapefile,
         left, bottom, right, top = src.bounds
         resolution = src.res[0]
 
+    # Check matching the crs
+    if not gdf.crs == src.crs:
+        raise ValueError("The shapefile crs {} does not match the image crs {}".format(
+            gdf.crs, src.crs))
+
     # Transform project coordinates to image coordinates
     df["tile_xmin"] = (df.minx - left) / resolution
     df["tile_xmin"] = df["tile_xmin"].astype(int)
@@ -389,7 +394,6 @@ def boxes_to_shapefile(df, root_dir, projected=True, flip_y_axis=False):
        df: a geospatial dataframe with the boxes optionally transformed to the target crs
     """
     # Raise a warning and confirm if a user sets projected to True when flip_y_axis is True.
-
     if flip_y_axis and projected:
         warnings.warn(
             "flip_y_axis is {}, and projected is {}. In most cases, projected should be False when inverting y axis. Setting projected=False"
@@ -473,10 +477,11 @@ def annotations_to_shapefile(df, transform, crs):
     Returns:
         results: a geopandas dataframe where every entry is the bounding box for a detected tree.
     """
-    warnings.warn("This method is deprecated and will be "
-                  "removed in version DeepForest 2.0.0, "
-                  "please use boxes_to_shapefile which unifies project_boxes and "
-                  "annotations_to_shapefile functionalities")
+    warnings.warn(
+        "This method is deprecated and will be "
+        "removed in version DeepForest 2.0.0, "
+        "please use boxes_to_shapefile which unifies project_boxes and "
+        "annotations_to_shapefile functionalities", DeprecationWarning)
 
     # Convert image pixel locations to geographic coordinates
     xmin_coords, ymin_coords = rasterio.transform.xy(transform=transform,
@@ -489,6 +494,13 @@ def annotations_to_shapefile(df, transform, crs):
                                                      cols=df.xmax,
                                                      offset='center')
 
+    # If there is only one tree, the above comes out as a float, not a list
+    if type(xmin_coords) == float:
+        xmin_coords = [xmin_coords]
+        ymin_coords = [ymin_coords]
+        xmax_coords = [xmax_coords]
+        ymax_coords = [ymax_coords]
+
     # One box polygon for each tree bounding box
     box_coords = zip(xmin_coords, ymin_coords, xmax_coords, ymax_coords)
     box_geoms = [
@@ -511,9 +523,11 @@ def project_boxes(df, root_dir, transform=True):
     root_dir: directory of images to lookup image_path column
     transform: If true, convert from image to geographic coordinates
     """
-    warnings.warn("This method is deprecated and will be removed in version "
-                  "DeepForest 2.0.0, please use boxes_to_shapefile which "
-                  "unifies project_boxes and annotations_to_shapefile functionalities")
+    warnings.warn(
+        "This method is deprecated and will be removed in version "
+        "DeepForest 2.0.0, please use boxes_to_shapefile which "
+        "unifies project_boxes and annotations_to_shapefile functionalities",
+        DeprecationWarning)
     plot_names = df.image_path.unique()
     if len(plot_names) > 1:
         raise ValueError("This function projects a single plots worth of data. "

tests/test_utilities.py

@@ -55,7 +55,7 @@ def test_shapefile_to_annotations_convert_to_boxes(tmpdir):
     sample_geometry = [geometry.Point(404211.9 + 10,3285102 + 20),geometry.Point(404211.9 + 20,3285102 + 20)]
     labels = ["Tree","Tree"]
     df = pd.DataFrame({"geometry":sample_geometry,"label":labels})
-    gdf = gpd.GeoDataFrame(df, geometry="geometry")
+    gdf = gpd.GeoDataFrame(df, geometry="geometry", crs="EPSG:32617")
     gdf.to_file("{}/annotations.shp".format(tmpdir))
     image_path = get_data("OSBS_029.tif")
     shp = utilities.shapefile_to_annotations(shapefile="{}/annotations.shp".format(tmpdir), rgb=image_path, savedir=tmpdir, geometry_type="point")
@@ -65,7 +65,7 @@ def test_shapefile_to_annotations(tmpdir):
     sample_geometry = [geometry.Point(404211.9 + 10,3285102 + 20),geometry.Point(404211.9 + 20,3285102 + 20)]
     labels = ["Tree","Tree"]
     df = pd.DataFrame({"geometry":sample_geometry,"label":labels})
-    gdf = gpd.GeoDataFrame(df, geometry="geometry")
+    gdf = gpd.GeoDataFrame(df, geometry="geometry", crs="EPSG:32617")
     gdf["geometry"] = [geometry.box(left, bottom, right, top) for left, bottom, right, top in gdf.geometry.buffer(0.5).bounds.values]
 
     gdf.to_file("{}/annotations.shp".format(tmpdir))
@@ -118,4 +118,4 @@ def test_boxes_to_shapefile_unprojected(m, flip_y_axis, projected):
 
     # Confirm that each boxes within image bounds
     geom = geometry.box(*r.bounds)
-    assert all(gdf.geometry.apply(lambda x: geom.intersects(geom)).values)
+    assert all(gdf.geometry.apply(lambda x: geom.intersects(geom)).values)