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Ultralytics Code Refactor https://ultralytics.com/actions (#13174)

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Refactor code for speed and clarity
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Glenn Jocher authored and GitHub committed 2024-07-08 21:19:04 +02:00
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detect.py
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@@ -97,7 +97,56 @@ def run(
dnn=False, # use OpenCV DNN for ONNX inference
vid_stride=1, # video frame-rate stride
):
"""Runs YOLOv5 detection inference on various sources like images, videos, directories, streams, etc."""
"""
Runs YOLOv5 detection inference on various sources like images, videos, directories, streams, etc.
Args:
weights (str | Path): Path to the model weights file or a Triton URL. Default is 'yolov5s.pt'.
source (str | Path): Input source, which can be a file, directory, URL, glob pattern, screen capture, or webcam index.
Default is 'data/images'.
data (str | Path): Path to the dataset YAML file. Default is 'data/coco128.yaml'.
imgsz (tuple[int, int]): Inference image size as a tuple (height, width). Default is (640, 640).
conf_thres (float): Confidence threshold for detections. Default is 0.25.
iou_thres (float): Intersection Over Union (IOU) threshold for non-max suppression. Default is 0.45.
max_det (int): Maximum number of detections per image. Default is 1000.
device (str): CUDA device identifier (e.g., '0' or '0,1,2,3') or 'cpu'. Default is an empty string, which
uses the best available device.
view_img (bool): If True, display inference results using OpenCV. Default is False.
save_txt (bool): If True, save results in a text file. Default is False.
save_csv (bool): If True, save results in a CSV file. Default is False.
save_conf (bool): If True, include confidence scores in the saved results. Default is False.
save_crop (bool): If True, save cropped prediction boxes. Default is False.
nosave (bool): If True, do not save inference images or videos. Default is False.
classes (list[int]): List of class indices to filter detections by. Default is None.
agnostic_nms (bool): If True, perform class-agnostic non-max suppression. Default is False.
augment (bool): If True, use augmented inference. Default is False.
visualize (bool): If True, visualize feature maps. Default is False.
update (bool): If True, update all models' weights. Default is False.
project (str | Path): Directory to save results. Default is 'runs/detect'.
name (str): Name of the current experiment; used to create a subdirectory within 'project'. Default is 'exp'.
exist_ok (bool): If True, existing directories with the same name are reused instead of being incremented. Default is
False.
line_thickness (int): Thickness of bounding box lines in pixels. Default is 3.
hide_labels (bool): If True, do not display labels on bounding boxes. Default is False.
hide_conf (bool): If True, do not display confidence scores on bounding boxes. Default is False.
half (bool): If True, use FP16 half-precision inference. Default is False.
dnn (bool): If True, use OpenCV DNN backend for ONNX inference. Default is False.
vid_stride (int): Stride for processing video frames, to skip frames between processing. Default is 1.
Returns:
None
Examples:
```python
from ultralytics import run
# Run inference on an image
run(source='data/images/example.jpg', weights='yolov5s.pt', device='0')
# Run inference on a video with specific confidence threshold
run(source='data/videos/example.mp4', weights='yolov5s.pt', conf_thres=0.4, device='0')
```
"""
source = str(source)
save_img = not nosave and not source.endswith(".txt") # save inference images
is_file = Path(source).suffix[1:] in (IMG_FORMATS + VID_FORMATS)
@@ -266,7 +315,48 @@ def run(
def parse_opt():
"""Parses command-line arguments for YOLOv5 detection, setting inference options and model configurations."""
"""
Parses command-line arguments for YOLOv5 detection, setting inference options and model configurations.
Args:
--weights (str | list[str], optional): Model path or Triton URL. Defaults to ROOT / 'yolov5s.pt'.
--source (str, optional): File/dir/URL/glob/screen/0(webcam). Defaults to ROOT / 'data/images'.
--data (str, optional): Dataset YAML path. Provides dataset configuration information.
--imgsz (list[int], optional): Inference size (height, width). Defaults to [640].
--conf-thres (float, optional): Confidence threshold. Defaults to 0.25.
--iou-thres (float, optional): NMS IoU threshold. Defaults to 0.45.
--max-det (int, optional): Maximum number of detections per image. Defaults to 1000.
--device (str, optional): CUDA device, i.e., '0' or '0,1,2,3' or 'cpu'. Defaults to "".
--view-img (bool, optional): Flag to display results. Defaults to False.
--save-txt (bool, optional): Flag to save results to *.txt files. Defaults to False.
--save-csv (bool, optional): Flag to save results in CSV format. Defaults to False.
--save-conf (bool, optional): Flag to save confidences in labels saved via --save-txt. Defaults to False.
--save-crop (bool, optional): Flag to save cropped prediction boxes. Defaults to False.
--nosave (bool, optional): Flag to prevent saving images/videos. Defaults to False.
--classes (list[int], optional): List of classes to filter results by, e.g., '--classes 0 2 3'. Defaults to None.
--agnostic-nms (bool, optional): Flag for class-agnostic NMS. Defaults to False.
--augment (bool, optional): Flag for augmented inference. Defaults to False.
--visualize (bool, optional): Flag for visualizing features. Defaults to False.
--update (bool, optional): Flag to update all models in the model directory. Defaults to False.
--project (str, optional): Directory to save results. Defaults to ROOT / 'runs/detect'.
--name (str, optional): Sub-directory name for saving results within --project. Defaults to 'exp'.
--exist-ok (bool, optional): Flag to allow overwriting if the project/name already exists. Defaults to False.
--line-thickness (int, optional): Thickness (in pixels) of bounding boxes. Defaults to 3.
--hide-labels (bool, optional): Flag to hide labels in the output. Defaults to False.
--hide-conf (bool, optional): Flag to hide confidences in the output. Defaults to False.
--half (bool, optional): Flag to use FP16 half-precision inference. Defaults to False.
--dnn (bool, optional): Flag to use OpenCV DNN for ONNX inference. Defaults to False.
--vid-stride (int, optional): Video frame-rate stride, determining the number of frames to skip in between consecutive frames. Defaults to 1.
Returns:
argparse.Namespace: Parsed command-line arguments as an argparse.Namespace object.
Example:
```python
from ultralytics import YOLOv5
args = YOLOv5.parse_opt()
```
"""
parser = argparse.ArgumentParser()
parser.add_argument("--weights", nargs="+", type=str, default=ROOT / "yolov5s.pt", help="model path or triton URL")
parser.add_argument("--source", type=str, default=ROOT / "data/images", help="file/dir/URL/glob/screen/0(webcam)")
@@ -303,7 +393,28 @@ def parse_opt():
def main(opt):
"""Executes YOLOv5 model inference with given options, checking requirements before running the model."""
"""
Executes YOLOv5 model inference based on provided command-line arguments, validating dependencies before running.
Args:
opt (argparse.Namespace): Command-line arguments for YOLOv5 detection. See function `parse_opt` for details.
Returns:
None
Note:
This function performs essential pre-execution checks and initiates the YOLOv5 detection process based on user-specified options.
Refer to the usage guide and examples for more information about different sources and formats at:
https://github.com/ultralytics/ultralytics
Example usage:
```python
if __name__ == "__main__":
opt = parse_opt()
main(opt)
```
"""
check_requirements(ROOT / "requirements.txt", exclude=("tensorboard", "thop"))
run(**vars(opt))