ultralytics 8.0.136 refactor and simplify package (#3748)

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

ultralytics/yolo/v8/detect/predict.py

@@ -1,48 +0,0 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-
-import torch
-
-from ultralytics.yolo.engine.predictor import BasePredictor
-from ultralytics.yolo.engine.results import Results
-from ultralytics.yolo.utils import DEFAULT_CFG, ROOT, ops
-
-
-class DetectionPredictor(BasePredictor):
-
-    def postprocess(self, preds, img, orig_imgs):
-        """Postprocesses predictions and returns a list of Results objects."""
-        preds = ops.non_max_suppression(preds,
-                                        self.args.conf,
-                                        self.args.iou,
-                                        agnostic=self.args.agnostic_nms,
-                                        max_det=self.args.max_det,
-                                        classes=self.args.classes)
-
-        results = []
-        for i, pred in enumerate(preds):
-            orig_img = orig_imgs[i] if isinstance(orig_imgs, list) else orig_imgs
-            if not isinstance(orig_imgs, torch.Tensor):
-                pred[:, :4] = ops.scale_boxes(img.shape[2:], pred[:, :4], orig_img.shape)
-            path = self.batch[0]
-            img_path = path[i] if isinstance(path, list) else path
-            results.append(Results(orig_img=orig_img, path=img_path, names=self.model.names, boxes=pred))
-        return results
-
-
-def predict(cfg=DEFAULT_CFG, use_python=False):
-    """Runs YOLO model inference on input image(s)."""
-    model = cfg.model or 'yolov8n.pt'
-    source = cfg.source if cfg.source is not None else ROOT / 'assets' if (ROOT / 'assets').exists() \
-        else 'https://ultralytics.com/images/bus.jpg'
-
-    args = dict(model=model, source=source)
-    if use_python:
-        from ultralytics import YOLO
-        YOLO(model)(**args)
-    else:
-        predictor = DetectionPredictor(overrides=args)
-        predictor.predict_cli()
-
-
-if __name__ == '__main__':
-    predict()