ultralytics 8.0.81 single-line docstring updates (#2061)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/engine/predictor.py

@@ -107,9 +107,11 @@ class BasePredictor:
         callbacks.add_integration_callbacks(self)
 
     def preprocess(self, img):
+        """Prepares input image before inference."""
         pass
 
     def write_results(self, idx, results, batch):
+        """Write inference results to a file or directory."""
         p, im, _ = batch
         log_string = ''
         if len(im.shape) == 3:
@@ -143,9 +145,11 @@ class BasePredictor:
         return log_string
 
     def postprocess(self, preds, img, orig_img):
+        """Post-processes predictions for an image and returns them."""
         return preds
 
     def __call__(self, source=None, model=None, stream=False):
+        """Performs inference on an image or stream."""
         self.stream = stream
         if stream:
             return self.stream_inference(source, model)
@@ -159,6 +163,7 @@ class BasePredictor:
             pass
 
     def setup_source(self, source):
+        """Sets up source and inference mode."""
         self.imgsz = check_imgsz(self.args.imgsz, stride=self.model.stride, min_dim=2)  # check image size
         if self.args.task == 'classify':
             transforms = getattr(self.model.model, 'transforms', classify_transforms(self.imgsz[0]))
@@ -179,6 +184,7 @@ class BasePredictor:
 
     @smart_inference_mode()
     def stream_inference(self, source=None, model=None):
+        """Streams real-time inference on camera feed and saves results to file."""
         if self.args.verbose:
             LOGGER.info('')
 
@@ -264,6 +270,7 @@ class BasePredictor:
         self.run_callbacks('on_predict_end')
 
     def setup_model(self, model, verbose=True):
+        """Initialize YOLO model with given parameters and set it to evaluation mode."""
         device = select_device(self.args.device, verbose=verbose)
         model = model or self.args.model
         self.args.half &= device.type != 'cpu'  # half precision only supported on CUDA
@@ -278,6 +285,7 @@ class BasePredictor:
         self.model.eval()
 
     def show(self, p):
+        """Display an image in a window using OpenCV imshow()."""
         im0 = self.plotted_img
         if platform.system() == 'Linux' and p not in self.windows:
             self.windows.append(p)
@@ -287,6 +295,7 @@ class BasePredictor:
         cv2.waitKey(500 if self.batch[4].startswith('image') else 1)  # 1 millisecond
 
     def save_preds(self, vid_cap, idx, save_path):
+        """Save video predictions as mp4 at specified path."""
         im0 = self.plotted_img
         # Save imgs
         if self.dataset.mode == 'image':
@@ -307,6 +316,7 @@ class BasePredictor:
             self.vid_writer[idx].write(im0)
 
     def run_callbacks(self, event: str):
+        """Runs all registered callbacks for a specific event."""
         for callback in self.callbacks.get(event, []):
             callback(self)