Refactor code for speed and clarity

ultralytics · Jul 5, 2024 · 2edd803 · 2edd803
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diff --git a/README.md b/README.md
@@ -5,7 +5,7 @@
 
 Welcome to the [Ultralytics xView YOLOv3](https://github.com/ultralytics/xview-yolov3) repository! Here we provide code to train the powerful YOLOv3 object detection model on the xView dataset for the [xView Challenge](https://challenge.xviewdataset.org/). This challenge focuses on detecting objects from satellite imagery, advancing the state of the art in computer vision applications for remote sensing.
 
-[![Ultralytics Actions](https://github.com/ultralytics/xview-yolov3/actions/workflows/format.yml/badge.svg)](https://github.com/ultralytics/xview-yolov3/actions/workflows/format.yml) <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
+[![Ultralytics Actions](https://github.com/ultralytics/xview-yolov3/actions/workflows/format.yml/badge.svg)](https://github.com/ultralytics/xview-yolov3/actions/workflows/format.yml) <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a> <a href="https://community.ultralytics.com"><img alt="Ultralytics Forums" src="https://img.shields.io/discourse/users?server=https%3A%2F%2Fcommunity.ultralytics.com&logo=discourse&label=Forums&color=blue"></a>
 
 <img src="https://github-production-user-asset-6210df.s3.amazonaws.com/26833433/238799379-bb3b02f0-dee4-4e67-80ae-4b2378b813ad.jpg?raw=true" width="100%">
 

diff --git a/models.py b/models.py
@@ -1,7 +1,6 @@
 from collections import defaultdict
 
 import torch.nn as nn
-
 from utils.utils import *
 
 

diff --git a/scoring/matching.py b/scoring/matching.py
@@ -16,7 +16,6 @@
 from collections import defaultdict
 
 import numpy as np
-
 from scoring.rectangle import Rectangle
 
 

diff --git a/scoring/score.py b/scoring/score.py
@@ -20,10 +20,9 @@
 
 import numpy as np
 import scipy.io
-from tqdm import tqdm
-
 from scoring.matching import Matching
 from scoring.rectangle import Rectangle
+from tqdm import tqdm
 
 """
   Scoring code to calculate per-class precision and mean average precision.

diff --git a/utils/datasets.py b/utils/datasets.py
@@ -301,6 +301,7 @@ def resize_square(img, height=416, color=(0, 0, 0)):  # resizes a rectangular im
 def random_affine(
     img, targets=None, degrees=(-10, 10), translate=(0.1, 0.1), scale=(0.9, 1.1), shear=(-3, 3), borderValue=(0, 0, 0)
 ):
+    """Performs random affine transformations on an image and its target annotations, including rotation, translation, scaling, and shearing."""
     # torchvision.transforms.RandomAffine(degrees=(-10, 10), translate=(.1, .1), scale=(.9, 1.1), shear=(-10, 10))
     # https://medium.com/uruvideo/dataset-augmentation-with-random-homographies-a8f4b44830d4
     border = 750

diff --git a/utils/utils.py b/utils/utils.py
@@ -517,6 +517,7 @@ def build_targets(pred_boxes, pred_conf, pred_cls, target, anchor_wh, nA, nC, nG
 
 
 def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4, mat=None, img=None, model2=None, device="cpu"):
+    """Performs Non-Maximum Suppression on detection results, filtering out low-confidence detections."""
     prediction = prediction.cpu()
     """
     Removes detections with lower object confidence score than 'conf_thres' and performs Non-Maximum Suppression to