Allow PyTorch Hub results to display in notebooks (#9825)

* Allow PyTorch Hub results to display in notebooks

* fix CI

* fix CI

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix CI

* fix CI

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix CI

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix CI

* fix CI

* fix CI

* fix CI

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix CI

* fix CI

* fix CI

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

models/common.py

@@ -18,16 +18,20 @@ import pandas as pd
 import requests
 import torch
 import torch.nn as nn
+from IPython.display import display
 from PIL import Image
 from torch.cuda import amp
 
+from utils import TryExcept
 from utils.dataloaders import exif_transpose, letterbox
-from utils.general import (LOGGER, ROOT, Profile, check_requirements, check_suffix, check_version, colorstr,
-                           increment_path, make_divisible, non_max_suppression, scale_boxes, xywh2xyxy, xyxy2xywh,
-                           yaml_load)
+from utils.general import (LOGGER, ROOT, Profile, check_imshow, check_requirements, check_suffix, check_version,
+                           colorstr, increment_path, make_divisible, non_max_suppression, scale_boxes, xywh2xyxy,
+                           xyxy2xywh, yaml_load)
 from utils.plots import Annotator, colors, save_one_box
 from utils.torch_utils import copy_attr, smart_inference_mode
 
+CHECK_IMSHOW = check_imshow()
+
 
 def autopad(k, p=None, d=1):  # kernel, padding, dilation
     # Pad to 'same' shape outputs
@@ -756,7 +760,7 @@ class Detections:
 
             im = Image.fromarray(im.astype(np.uint8)) if isinstance(im, np.ndarray) else im  # from np
             if show:
-                im.show(self.files[i])  # show
+                im.show(self.files[i]) if CHECK_IMSHOW else display(im)
             if save:
                 f = self.files[i]
                 im.save(save_dir / f)  # save
@@ -772,6 +776,7 @@ class Detections:
                 LOGGER.info(f'Saved results to {save_dir}\n')
             return crops
 
+    @TryExcept('Showing images is not supported in this environment')
     def show(self, labels=True):
         self._run(show=True, labels=labels)  # show results