ultralytics 8.1.3 ResNet models and lighter dependencies (#7700)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Vivek Malvi <vivekmalvi@raoinformationtechnology.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: iscyy <wenvoi@163.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Prince kumar <85225054+prince0310@users.noreply.github.com>

.github/workflows/format.yml

@@ -23,7 +23,7 @@ jobs:
           markdown: true # format Markdown and YAML
           spelling: true # check spelling
           links: false # check broken links
-          summary: true  # print PR summary with GPT4 (requires 'openai_api_key' or 'openai_azure_api_key' and 'openai_azure_endpoint')
+          summary: true # print PR summary with GPT4 (requires 'openai_api_key' or 'openai_azure_api_key' and 'openai_azure_endpoint')
           openai_azure_api_key: ${{ secrets.OPENAI_AZURE_API_KEY }}
           openai_azure_endpoint: ${{ secrets.OPENAI_AZURE_ENDPOINT }}
           # openai_api_key: ${{ secrets.OPENAI_API_KEY }}

docs/mkdocs.yml

@@ -71,40 +71,40 @@ extra: # version:
   analytics:
     provider: google
     property: G-2M5EHKC0BH
-#  alternate: # language drop-down
-#    - name: 🇬🇧 English
-#      link: /
-#      lang: en
-#    - name: 🇨🇳 简体中文
-#      link: /zh/
-#      lang: zh
-#    - name: 🇰🇷 한국어
-#      link: /ko/
-#      lang: ko
-#    - name: 🇯🇵 日本語
-#      link: /ja/
-#      lang: ja
-#    - name: 🇷🇺 Русский
-#      link: /ru/
-#      lang: ru
-#    - name: 🇩🇪 Deutsch
-#      link: /de/
-#      lang: de
-#    - name: 🇫🇷 Français
-#      link: /fr/
-#      lang: fr
-#    - name: 🇪🇸 Español
-#      link: /es/
-#      lang: es
-#    - name: 🇵🇹 Português
-#      link: /pt/
-#      lang: pt
-#    - name: 🇮🇳 हिन्दी
-#      link: /hi/
-#      lang: hi
-#    - name: 🇸🇦 العربية
-#      link: /ar/
-#      lang: ar
+  #  alternate: # language drop-down
+  #    - name: 🇬🇧 English
+  #      link: /
+  #      lang: en
+  #    - name: 🇨🇳 简体中文
+  #      link: /zh/
+  #      lang: zh
+  #    - name: 🇰🇷 한국어
+  #      link: /ko/
+  #      lang: ko
+  #    - name: 🇯🇵 日本語
+  #      link: /ja/
+  #      lang: ja
+  #    - name: 🇷🇺 Русский
+  #      link: /ru/
+  #      lang: ru
+  #    - name: 🇩🇪 Deutsch
+  #      link: /de/
+  #      lang: de
+  #    - name: 🇫🇷 Français
+  #      link: /fr/
+  #      lang: fr
+  #    - name: 🇪🇸 Español
+  #      link: /es/
+  #      lang: es
+  #    - name: 🇵🇹 Português
+  #      link: /pt/
+  #      lang: pt
+  #    - name: 🇮🇳 हिन्दी
+  #      link: /hi/
+  #      lang: hi
+  #    - name: 🇸🇦 العربية
+  #      link: /ar/
+  #      lang: ar
   social:
     - icon: fontawesome/brands/github
       link: https://github.com/ultralytics

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.1.2"
+__version__ = "8.1.3"
 
 from ultralytics.data.explorer.explorer import Explorer
 from ultralytics.models import RTDETR, SAM, YOLO

ultralytics/cfg/models/v8/yolov8-cls-resnet101.yaml

@@ -0,0 +1,25 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 license
+# YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
+
+# Parameters
+nc: 1000 # number of classes
+scales: # model compound scaling constants, i.e. 'model=yolov8n-cls.yaml' will call yolov8-cls.yaml with scale 'n'
+  # [depth, width, max_channels]
+  n: [0.33, 0.25, 1024]
+  s: [0.33, 0.50, 1024]
+  m: [0.67, 0.75, 1024]
+  l: [1.00, 1.00, 1024]
+  x: [1.00, 1.25, 1024]
+
+# YOLOv8.0n backbone
+backbone:
+  # [from, repeats, module, args]
+  - [-1, 1, ResNetLayer, [3, 64, 1, True, 1]] # 0-P1/2
+  - [-1, 1, ResNetLayer, [64, 64, 1, False, 3]] # 1-P2/4
+  - [-1, 1, ResNetLayer, [256, 128, 2, False, 4]] # 2-P3/8
+  - [-1, 1, ResNetLayer, [512, 256, 2, False, 23]] # 3-P4/16
+  - [-1, 1, ResNetLayer, [1024, 512, 2, False, 3]] # 4-P5/32
+
+# YOLOv8.0n head
+head:
+  - [-1, 1, Classify, [nc]] # Classify

ultralytics/cfg/models/v8/yolov8-cls-resnet50.yaml

@@ -0,0 +1,25 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 license
+# YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
+
+# Parameters
+nc: 1000 # number of classes
+scales: # model compound scaling constants, i.e. 'model=yolov8n-cls.yaml' will call yolov8-cls.yaml with scale 'n'
+  # [depth, width, max_channels]
+  n: [0.33, 0.25, 1024]
+  s: [0.33, 0.50, 1024]
+  m: [0.67, 0.75, 1024]
+  l: [1.00, 1.00, 1024]
+  x: [1.00, 1.25, 1024]
+
+# YOLOv8.0n backbone
+backbone:
+  # [from, repeats, module, args]
+  - [-1, 1, ResNetLayer, [3, 64, 1, True, 1]] # 0-P1/2
+  - [-1, 1, ResNetLayer, [64, 64, 1, False, 3]] # 1-P2/4
+  - [-1, 1, ResNetLayer, [256, 128, 2, False, 4]] # 2-P3/8
+  - [-1, 1, ResNetLayer, [512, 256, 2, False, 6]] # 3-P4/16
+  - [-1, 1, ResNetLayer, [1024, 512, 2, False, 3]] # 4-P5/32
+
+# YOLOv8.0n head
+head:
+  - [-1, 1, Classify, [nc]] # Classify

ultralytics/engine/model.py

@@ -52,13 +52,14 @@ class Model(nn.Module):
         list(ultralytics.engine.results.Results): The prediction results.
     """
 
-    def __init__(self, model: Union[str, Path] = "yolov8n.pt", task=None) -> None:
+    def __init__(self, model: Union[str, Path] = "yolov8n.pt", task=None, verbose=False) -> None:
         """
         Initializes the YOLO model.
 
         Args:
             model (Union[str, Path], optional): Path or name of the model to load or create. Defaults to 'yolov8n.pt'.
             task (Any, optional): Task type for the YOLO model. Defaults to None.
+            verbose (bool, optional): Whether to enable verbose mode.
         """
         super().__init__()
         self.callbacks = callbacks.get_default_callbacks()
@@ -77,6 +78,7 @@ class Model(nn.Module):
         # Check if Ultralytics HUB model from https://hub.ultralytics.com
         if self.is_hub_model(model):
             # Fetch model from HUB
+            checks.check_requirements("hub-sdk>0.0.2")
             self.session = self._get_hub_session(model)
             model = self.session.model_file
 
@@ -89,9 +91,9 @@ class Model(nn.Module):
         # Load or create new YOLO model
         model = checks.check_model_file_from_stem(model)  # add suffix, i.e. yolov8n -> yolov8n.pt
         if Path(model).suffix in (".yaml", ".yml"):
-            self._new(model, task)
+            self._new(model, task=task, verbose=verbose)
         else:
-            self._load(model, task)
+            self._load(model, task=task)
 
         self.model_name = model
 
@@ -126,7 +128,7 @@ class Model(nn.Module):
             )
         )
 
-    def _new(self, cfg: str, task=None, model=None, verbose=True):
+    def _new(self, cfg: str, task=None, model=None, verbose=False):
         """
         Initializes a new model and infers the task type from the model definitions.
 
@@ -381,8 +383,8 @@ class Model(nn.Module):
                         # Check model was created
                         if not getattr(self.session.model, "id", None):
                             self.session = None
-                except PermissionError:
-                    # Ignore permission error
+                except (PermissionError, ModuleNotFoundError):
+                    # Ignore PermissionError and ModuleNotFoundError which indicates hub-sdk not installed
                     pass
 
         self.trainer.hub_session = self.session  # attach optional HUB session

ultralytics/hub/session.py

@@ -42,8 +42,8 @@ class HUBTrainingSession:
         Raises:
             ValueError: If the provided model identifier is invalid.
             ConnectionError: If connecting with global API key is not supported.
+            ModuleNotFoundError: If hub-sdk package is not installed.
         """
-        checks.check_requirements("hub-sdk>=0.0.2")
         from hub_sdk import HUBClient
 
         self.rate_limits = {

ultralytics/utils/plotting.py

@@ -256,7 +256,7 @@ class Annotator:
             # Convert to numpy first
             self.im = np.asarray(self.im).copy()
         nkpt, ndim = kpts.shape
-        is_pose = nkpt == 17 and ndim == 3
+        is_pose = nkpt == 17 and ndim in {2, 3}
         kpt_line &= is_pose  # `kpt_line=True` for now only supports human pose plotting
         for i, k in enumerate(kpts):
             color_k = [int(x) for x in self.kpt_color[i]] if is_pose else colors(i)