Unified hub and detect.py box and labels plotting (#2243)

models/common.py

 
 from utils.datasets import letterbox
 from utils.general import non_max_suppression, make_divisible, scale_coords, xyxy2xywh
-from utils.plots import color_list
+from utils.plots import color_list, plot_one_box
 
 
 def autopad(k, p=None):  # kernel, padding
                     n = (pred[:, -1] == c).sum()  # detections per class
                     str += f"{n} {self.names[int(c)]}{'s' * (n > 1)}, "  # add to string
                 if show or save or render:
-                    img = Image.fromarray(img.astype(np.uint8)) if isinstance(img, np.ndarray) else img  # from np
                     for *box, conf, cls in pred:  # xyxy, confidence, class
-                        # str += '%s %.2f, ' % (names[int(cls)], conf)  # label
-                        ImageDraw.Draw(img).rectangle(box, width=4, outline=colors[int(cls) % 10])  # plot
+                        label = f'{self.names[int(cls)]} {conf:.2f}'
+                        plot_one_box(box, img, label=label, color=colors[int(cls) % 10])
+            img = Image.fromarray(img.astype(np.uint8)) if isinstance(img, np.ndarray) else img  # from np
             if pprint:
                 print(str.rstrip(', '))
             if show: