Merge remote-tracking branch 'origin/docstrings' into docstrings

classify/train.py

@@ -307,7 +307,9 @@ def train(opt, device):
 
 
 def parse_opt(known=False):
-    """Parses command line arguments for YOLOv5 training including model path, dataset, epochs, and more, returning parsed arguments."""
+    """Parses command line arguments for YOLOv5 training including model path, dataset, epochs, and more, returning
+    parsed arguments.
+    """
     parser = argparse.ArgumentParser()
     parser.add_argument("--model", type=str, default="yolov5s-cls.pt", help="initial weights path")
     parser.add_argument("--data", type=str, default="imagenette160", help="cifar10, cifar100, mnist, imagenet, ...")
@@ -359,9 +361,11 @@ def main(opt):
 
 
 def run(**kwargs):
-    """Executes YOLOv5 model training or inference with specified parameters, returning updated options.
+    """
+    Executes YOLOv5 model training or inference with specified parameters, returning updated options.
 
-    Example: from yolov5 import classify; classify.train.run(data=mnist, imgsz=320, model='yolov5m')"""
+    Example: from yolov5 import classify; classify.train.run(data=mnist, imgsz=320, model='yolov5m')
+    """
     opt = parse_opt(True)
     for k, v in kwargs.items():
         setattr(opt, k, v)

segment/predict.py

@@ -257,7 +257,9 @@ def run(
 
 
 def parse_opt():
-    """Parses command-line options for YOLOv5 inference including model paths, data sources, inference settings, and output preferences."""
+    """Parses command-line options for YOLOv5 inference including model paths, data sources, inference settings, and
+    output preferences.
+    """
     parser = argparse.ArgumentParser()
     parser.add_argument("--weights", nargs="+", type=str, default=ROOT / "yolov5s-seg.pt", help="model path(s)")
     parser.add_argument("--source", type=str, default=ROOT / "data/images", help="file/dir/URL/glob/screen/0(webcam)")

segment/train.py

@@ -532,7 +532,11 @@ def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictio
 
 
 def parse_opt(known=False):
-    """Parses command line arguments for training configurations, returning parsed arguments. Supports both known and unknown args."""
+    """
+    Parses command line arguments for training configurations, returning parsed arguments.
+
+    Supports both known and unknown args.
+    """
     parser = argparse.ArgumentParser()
     parser.add_argument("--weights", type=str, default=ROOT / "yolov5s-seg.pt", help="initial weights path")
     parser.add_argument("--cfg", type=str, default="", help="model.yaml path")
@@ -734,9 +738,11 @@ def main(opt, callbacks=Callbacks()):
 
 
 def run(**kwargs):
-    """Executes YOLOv5 training with given parameters, altering options programmatically; returns updated options.
+    """
+    Executes YOLOv5 training with given parameters, altering options programmatically; returns updated options.
 
-    Example: mport train; train.run(data='coco128.yaml', imgsz=320, weights='yolov5m.pt')"""
+    Example: mport train; train.run(data='coco128.yaml', imgsz=320, weights='yolov5m.pt')
+    """
     opt = parse_opt(True)
     for k, v in kwargs.items():
         setattr(opt, k, v)

utils/flask_rest_api/restapi.py

@@ -16,7 +16,9 @@
 
 @app.route(DETECTION_URL, methods=["POST"])
 def predict(model):
-    """Predict and return object detections in JSON format given an image and model name via a Flask REST API POST request."""
+    """Predict and return object detections in JSON format given an image and model name via a Flask REST API POST
+    request.
+    """
     if request.method != "POST":
         return
 

utils/segment/plots.py

@@ -111,7 +111,8 @@ def plot_images_and_masks(images, targets, masks, paths=None, fname="images.jpg"
 
 
 def plot_results_with_masks(file="path/to/results.csv", dir="", best=True):
-    """Plots training results from CSV files, plotting best or last result highlights based on `best` parameter.
+    """
+    Plots training results from CSV files, plotting best or last result highlights based on `best` parameter.
 
     Example: from utils.plots import *; plot_results('path/to/results.csv')
     """