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/models/nas/predict.py

@@ -0,0 +1,35 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 license
+
+import torch
+
+from ultralytics.engine.predictor import BasePredictor
+from ultralytics.engine.results import Results
+from ultralytics.utils import ops
+from ultralytics.utils.ops import xyxy2xywh
+
+
+class NASPredictor(BasePredictor):
+
+    def postprocess(self, preds_in, img, orig_imgs):
+        """Postprocesses predictions and returns a list of Results objects."""
+
+        # Cat boxes and class scores
+        boxes = xyxy2xywh(preds_in[0][0])
+        preds = torch.cat((boxes, preds_in[0][1]), -1).permute(0, 2, 1)
+
+        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