ultralytics 8.0.40 TensorRT metadata and Results visualizer (#1014)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Bogdan Gheorghe <112427971+bogdan-galileo@users.noreply.github.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: Jaap van de Loosdrecht <jaap@vdlmv.nl>
Co-authored-by: Noobtoss <96134731+Noobtoss@users.noreply.github.com>
Co-authored-by: nerdyespresso <106761627+nerdyespresso@users.noreply.github.com>

ultralytics/yolo/utils/__init__.py

@@ -34,6 +34,7 @@ AUTOINSTALL = str(os.getenv('YOLO_AUTOINSTALL', True)).lower() == 'true'  # glob
 VERBOSE = str(os.getenv('YOLO_VERBOSE', True)).lower() == 'true'  # global verbose mode
 TQDM_BAR_FORMAT = '{l_bar}{bar:10}{r_bar}'  # tqdm bar format
 LOGGING_NAME = 'ultralytics'
+MACOS, LINUX, WINDOWS = (platform.system() == x for x in ['Darwin', 'Linux', 'Windows'])  # environment booleans
 HELP_MSG = \
     """
     Usage examples for running YOLOv8:
@@ -393,18 +394,15 @@ def get_user_config_dir(sub_dir='Ultralytics'):
     Returns:
         Path: The path to the user config directory.
     """
-    # Get the operating system name
-    os_name = platform.system()
-
     # Return the appropriate config directory for each operating system
-    if os_name == 'Windows':
+    if WINDOWS:
         path = Path.home() / 'AppData' / 'Roaming' / sub_dir
-    elif os_name == 'Darwin':  # macOS
+    elif MACOS:  # macOS
         path = Path.home() / 'Library' / 'Application Support' / sub_dir
-    elif os_name == 'Linux':
+    elif LINUX:
         path = Path.home() / '.config' / sub_dir
     else:
-        raise ValueError(f'Unsupported operating system: {os_name}')
+        raise ValueError(f'Unsupported operating system: {platform.system()}')
 
     # GCP and AWS lambda fix, only /tmp is writeable
     if not is_dir_writeable(str(path.parent)):
@@ -421,7 +419,7 @@ USER_CONFIG_DIR = get_user_config_dir()  # Ultralytics settings dir
 
 def emojis(string=''):
     # Return platform-dependent emoji-safe version of string
-    return string.encode().decode('ascii', 'ignore') if platform.system() == 'Windows' else string
+    return string.encode().decode('ascii', 'ignore') if WINDOWS else string
 
 
 def colorstr(*input):
@@ -617,7 +615,7 @@ def set_settings(kwargs, file=USER_CONFIG_DIR / 'settings.yaml'):
 # Set logger
 set_logging(LOGGING_NAME)  # run before defining LOGGER
 LOGGER = logging.getLogger(LOGGING_NAME)  # define globally (used in train.py, val.py, detect.py, etc.)
-if platform.system() == 'Windows':
+if WINDOWS:
     for fn in LOGGER.info, LOGGER.warning:
         setattr(LOGGER, fn.__name__, lambda x: fn(emojis(x)))  # emoji safe logging
 

ultralytics/yolo/utils/ops.py

@@ -139,6 +139,9 @@ def non_max_suppression(
         labels=(),
         max_det=300,
         nc=0,  # number of classes (optional)
+        max_time_img=0.05,
+        max_nms=30000,
+        max_wh=7680,
 ):
     """
     Perform non-maximum suppression (NMS) on a set of boxes, with support for masks and multiple labels per box.
@@ -160,6 +163,9 @@ def non_max_suppression(
             output by a dataloader, with each label being a tuple of (class_index, x1, y1, x2, y2).
         max_det (int): The maximum number of boxes to keep after NMS.
         nc (int): (optional) The number of classes output by the model. Any indices after this will be considered masks.
+        max_time_img (float): The maximum time (seconds) for processing one image.
+        max_nms (int): The maximum number of boxes into torchvision.ops.nms().
+        max_wh (int): The maximum box width and height in pixels
 
     Returns:
         (List[torch.Tensor]): A list of length batch_size, where each element is a tensor of
@@ -185,9 +191,7 @@ def non_max_suppression(
 
     # Settings
     # min_wh = 2  # (pixels) minimum box width and height
-    max_wh = 7680  # (pixels) maximum box width and height
-    max_nms = 30000  # maximum number of boxes into torchvision.ops.nms()
-    time_limit = 0.5 + 0.05 * bs  # seconds to quit after
+    time_limit = 0.5 + max_time_img * bs  # seconds to quit after
     redundant = True  # require redundant detections
     multi_label &= nc > 1  # multiple labels per box (adds 0.5ms/img)
     merge = False  # use merge-NMS

ultralytics/yolo/utils/plotting.py

@@ -136,7 +136,11 @@ class Annotator:
         if anchor == 'bottom':  # start y from font bottom
             w, h = self.font.getsize(text)  # text width, height
             xy[1] += 1 - h
-        self.draw.text(xy, text, fill=txt_color, font=self.font)
+        if self.pil:
+            self.draw.text(xy, text, fill=txt_color, font=self.font)
+        else:
+            tf = max(self.lw - 1, 1)  # font thickness
+            cv2.putText(self.im, text, xy, 0, self.lw / 3, txt_color, thickness=tf, lineType=cv2.LINE_AA)
 
     def fromarray(self, im):
         # Update self.im from a numpy array