From bd84184b585e4ebb24a934fb4c37e0b03e7cac86 Mon Sep 17 00:00:00 2001
From: bw4sz <benweinstein2010@gmail.com>
Date: Tue, 5 Dec 2023 10:42:10 -0800
Subject: [PATCH] Style changes

---
 deepforest/main.py       | 16 ++++++++--------
 deepforest/predict.py    | 16 ++++++++--------
 deepforest/preprocess.py | 14 +++++++-------
 3 files changed, 23 insertions(+), 23 deletions(-)

diff --git a/deepforest/main.py b/deepforest/main.py
index bf66f368..6157ebed 100644
--- a/deepforest/main.py
+++ b/deepforest/main.py
@@ -372,14 +372,14 @@ def predict_file(self, csv_file, root_dir, savedir=None, color=None, thickness=1
         dataloader = self.predict_dataloader(ds)
 
         results = predict._dataloader_wrapper_(model=self,
-                                                 trainer=self.trainer,
-                                                 annotations=df,
-                                                 dataloader=dataloader,
-                                                 root_dir=root_dir,
-                                                 nms_thresh=self.config["nms_thresh"],
-                                                 savedir=savedir,
-                                                 color=color,
-                                                 thickness=thickness)
+                                               trainer=self.trainer,
+                                               annotations=df,
+                                               dataloader=dataloader,
+                                               root_dir=root_dir,
+                                               nms_thresh=self.config["nms_thresh"],
+                                               savedir=savedir,
+                                               color=color,
+                                               thickness=thickness)
 
         return results
 
diff --git a/deepforest/predict.py b/deepforest/predict.py
index 79254e91..fb92308e 100644
--- a/deepforest/predict.py
+++ b/deepforest/predict.py
@@ -134,14 +134,14 @@ def across_class_nms(predicted_boxes, iou_threshold=0.15):
 
 
 def _dataloader_wrapper_(model,
-                           trainer,
-                           dataloader,
-                           root_dir,
-                           annotations,
-                           nms_thresh,
-                           savedir=None,
-                           color=None,
-                           thickness=1):
+                         trainer,
+                         dataloader,
+                         root_dir,
+                         annotations,
+                         nms_thresh,
+                         savedir=None,
+                         color=None,
+                         thickness=1):
     """Create a dataset and predict entire annotation file
 
     Csv file format is .csv file with the columns "image_path", "xmin","ymin","xmax","ymax" for the image name and bounding box position.
diff --git a/deepforest/preprocess.py b/deepforest/preprocess.py
index 0c8ca86f..07a23328 100644
--- a/deepforest/preprocess.py
+++ b/deepforest/preprocess.py
@@ -146,8 +146,7 @@ def split_raster(annotations_file,
                  patch_overlap=0.05,
                  allow_empty=False,
                  image_name=None,
-                 save_dir="."
-                 ):
+                 save_dir="."):
     """Divide a large tile into smaller arrays. Each crop will be saved to
     file.
 
@@ -190,15 +189,16 @@ def split_raster(annotations_file,
     # Confirm that raster is H x W x C, if not, convert, assuming image is wider/taller than channels
     if numpy_image.shape[0] < numpy_image.shape[-1]:
         warnings.warn(
-            "Input rasterio had shape {}, assuming channels first. Converting to channels last".format(
-                numpy_image.shape), UserWarning)
+            "Input rasterio had shape {}, assuming channels first. Converting to channels last"
+            .format(numpy_image.shape), UserWarning)
         numpy_image = np.moveaxis(numpy_image, 0, 2)
-    
+
     # Check that its 3 band
     bands = numpy_image.shape[2]
     if not bands == 3:
-        warnings.warn("Input rasterio had non-3 band shape of {}, ignoring "
-                      "alpha channel".format(numpy_image.shape), UserWarning)
+        warnings.warn(
+            "Input rasterio had non-3 band shape of {}, ignoring "
+            "alpha channel".format(numpy_image.shape), UserWarning)
         try:
             numpy_image = numpy_image[:, :, :3].astype("uint8")
         except: