Check for broken links (#1422)

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

ultralytics/nn/autobackend.py

@@ -258,7 +258,7 @@ class AutoBackend(nn.Module):
         else:
             from ultralytics.yolo.engine.exporter import export_formats
             raise TypeError(f"model='{w}' is not a supported model format. "
-                            'See https://docs.ultralytics.com/tasks/detection/#export for help.'
+                            'See https://docs.ultralytics.com/modes/predict for help.'
                             f'\n\n{export_formats()}')
 
         # Load external metadata YAML

ultralytics/yolo/cfg/__init__.py

@@ -20,7 +20,7 @@ CLI_HELP_MSG = \
         Where   TASK (optional) is one of [detect, segment, classify]
                 MODE (required) is one of [train, val, predict, export, track]
                 ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.
-                    See all ARGS at https://docs.ultralytics.com/cfg or with 'yolo cfg'
+                    See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg'
 
     1. Train a detection model for 10 epochs with an initial learning_rate of 0.01
         yolo train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01
@@ -42,7 +42,7 @@ CLI_HELP_MSG = \
         yolo copy-cfg
         yolo cfg
 
-    Docs: https://docs.ultralytics.com/cli
+    Docs: https://docs.ultralytics.com
     Community: https://community.ultralytics.com
     GitHub: https://github.com/ultralytics/ultralytics
     """

ultralytics/yolo/data/build.py

@@ -153,7 +153,7 @@ def check_source(source):
     elif isinstance(source, torch.Tensor):
         tensor = True
     else:
-        raise TypeError('Unsupported image type. See docs for supported types https://docs.ultralytics.com/predict')
+        raise TypeError('Unsupported image type. For supported types see https://docs.ultralytics.com/modes/predict')
 
     return source, webcam, screenshot, from_img, in_memory, tensor
 

ultralytics/yolo/data/dataloaders/stream_loaders.py

@@ -359,7 +359,7 @@ def autocast_list(source):
             files.append(im)
         else:
             raise TypeError(f'type {type(im).__name__} is not a supported Ultralytics prediction source type. \n'
-                            f'See https://docs.ultralytics.com/predict for supported source types.')
+                            f'See https://docs.ultralytics.com/modes/predict for supported source types.')
 
     return files
 

ultralytics/yolo/utils/__init__.py

@@ -64,7 +64,7 @@ HELP_MSG = \
             Where   TASK (optional) is one of [detect, segment, classify]
                     MODE (required) is one of [train, val, predict, export]
                     ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.
-                        See all ARGS at https://docs.ultralytics.com/cfg or with 'yolo cfg'
+                        See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg'
 
         - Train a detection model for 10 epochs with an initial learning_rate of 0.01
             yolo detect train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01

ultralytics/yolo/v8/segment/train.py

@@ -88,7 +88,7 @@ class SegLoss(Loss):
                             "This error can occur when incorrectly training a 'segment' model on a 'detect' dataset, "
                             "i.e. 'yolo train model=yolov8n-seg.pt data=coco128.yaml'.\nVerify your dataset is a "
                             "correctly formatted 'segment' dataset using 'data=coco128-seg.yaml' "
-                            'as an example.\nSee https://docs.ultralytics.com/tasks/segmentation/ for help.') from e
+                            'as an example.\nSee https://docs.ultralytics.com/tasks/segment/ for help.') from e
 
         # pboxes
         pred_bboxes = self.bbox_decode(anchor_points, pred_distri)  # xyxy, (b, h*w, 4)