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Add type for train arguments (ultralytics#18221)
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Co-authored-by: UltralyticsAssistant <[email protected]>
Co-authored-by: Glenn Jocher <[email protected]>
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@RizwanMunawar @UltralyticsAssistant
@glenn-jocher @Y-T-G
3 people authored and Y-T-G committed Dec 17, 2024
1 parent 251c658 commit 295658a
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2 changes: 1 addition & 1 deletion docs/en/guides/object-counting.md
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Expand Up @@ -80,7 +80,7 @@ Object counting with [Ultralytics YOLO11](https://github.com/ultralytics/ultraly
# Video writer
video_writer = cv2.VideoWriter("object_counting_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))

# Init Object Counter
# Init ObjectCounter
counter = solutions.ObjectCounter(
show=True, # Display the output
region=region_points, # Pass region points
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2 changes: 1 addition & 1 deletion docs/en/guides/region-counting.md
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Expand Up @@ -59,7 +59,7 @@ keywords: object counting, regions, YOLOv8, computer vision, Ultralytics, effici
# Video writer
video_writer = cv2.VideoWriter("region_counting.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))

# Init Object Counter
# Init RegionCounter
region = solutions.RegionCounter(
show=True,
region=region_points,
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40 changes: 20 additions & 20 deletions docs/en/macros/predict-args.md
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@@ -1,20 +1,20 @@
| Argument | Type | Default | Description |
| --------------- | -------------- | ---------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `source` | `str` | `'ultralytics/assets'` | Specifies the data source for inference. Can be an image path, video file, directory, URL, or device ID for live feeds. Supports a wide range of formats and sources, enabling flexible application across [different types of input](/modes/predict.md/#inference-sources). |
| `conf` | `float` | `0.25` | Sets the minimum confidence threshold for detections. Objects detected with confidence below this threshold will be disregarded. Adjusting this value can help reduce false positives. |
| `iou` | `float` | `0.7` | [Intersection Over Union](https://www.ultralytics.com/glossary/intersection-over-union-iou) (IoU) threshold for Non-Maximum Suppression (NMS). Lower values result in fewer detections by eliminating overlapping boxes, useful for reducing duplicates. |
| `imgsz` | `int or tuple` | `640` | Defines the image size for inference. Can be a single integer `640` for square resizing or a (height, width) tuple. Proper sizing can improve detection [accuracy](https://www.ultralytics.com/glossary/accuracy) and processing speed. |
| `half` | `bool` | `False` | Enables half-[precision](https://www.ultralytics.com/glossary/precision) (FP16) inference, which can speed up model inference on supported GPUs with minimal impact on accuracy. |
| `device` | `str` | `None` | Specifies the device for inference (e.g., `cpu`, `cuda:0` or `0`). Allows users to select between CPU, a specific GPU, or other compute devices for model execution. |
| `batch` | `int` | `1` | Specifies the batch size for inference (only works when the source is [a directory, video file or `.txt` file](/modes/predict.md/#inference-sources)). A larger batch size can provide higher throughput, shortening the total amount of time required for inference. |
| `max_det` | `int` | `300` | Maximum number of detections allowed per image. Limits the total number of objects the model can detect in a single inference, preventing excessive outputs in dense scenes. |
| `vid_stride` | `int` | `1` | Frame stride for video inputs. Allows skipping frames in videos to speed up processing at the cost of temporal resolution. A value of 1 processes every frame, higher values skip frames. |
| `stream_buffer` | `bool` | `False` | Determines whether to queue incoming frames for video streams. If `False`, old frames get dropped to accomodate new frames (optimized for real-time applications). If `True', queues new frames in a buffer, ensuring no frames get skipped, but will cause latency if inference FPS is lower than stream FPS. |
| `visualize` | `bool` | `False` | Activates visualization of model features during inference, providing insights into what the model is "seeing". Useful for debugging and model interpretation. |
| `augment` | `bool` | `False` | Enables test-time augmentation (TTA) for predictions, potentially improving detection robustness at the cost of inference speed. |
| `agnostic_nms` | `bool` | `False` | Enables class-agnostic Non-Maximum Suppression (NMS), which merges overlapping boxes of different classes. Useful in multi-class detection scenarios where class overlap is common. |
| `classes` | `list[int]` | `None` | Filters predictions to a set of class IDs. Only detections belonging to the specified classes will be returned. Useful for focusing on relevant objects in multi-class detection tasks. |
| `retina_masks` | `bool` | `False` | Returns high-resolution segmentation masks. The returned masks (`masks.data`) will match the original image size if enabled. If disabled, they have the image size used during inference. |
| `embed` | `list[int]` | `None` | Specifies the layers from which to extract feature vectors or [embeddings](https://www.ultralytics.com/glossary/embeddings). Useful for downstream tasks like clustering or similarity search. |
| `project` | `str` | `None` | Name of the project directory where prediction outputs are saved if `save` is enabled. |
| `name` | `str` | `None` | Name of the prediction run. Used for creating a subdirectory within the project folder, where prediction outputs are stored if `save` is enabled. |
| Argument | Type | Default | Description |
| --------------- | ---------------- | ---------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `source` | `str` | `'ultralytics/assets'` | Specifies the data source for inference. Can be an image path, video file, directory, URL, or device ID for live feeds. Supports a wide range of formats and sources, enabling flexible application across [different types of input](/modes/predict.md/#inference-sources). |
| `conf` | `float` | `0.25` | Sets the minimum confidence threshold for detections. Objects detected with confidence below this threshold will be disregarded. Adjusting this value can help reduce false positives. |
| `iou` | `float` | `0.7` | [Intersection Over Union](https://www.ultralytics.com/glossary/intersection-over-union-iou) (IoU) threshold for Non-Maximum Suppression (NMS). Lower values result in fewer detections by eliminating overlapping boxes, useful for reducing duplicates. |
| `imgsz` | `int` or `tuple` | `640` | Defines the image size for inference. Can be a single integer `640` for square resizing or a (height, width) tuple. Proper sizing can improve detection [accuracy](https://www.ultralytics.com/glossary/accuracy) and processing speed. |
| `half` | `bool` | `False` | Enables half-[precision](https://www.ultralytics.com/glossary/precision) (FP16) inference, which can speed up model inference on supported GPUs with minimal impact on accuracy. |
| `device` | `str` | `None` | Specifies the device for inference (e.g., `cpu`, `cuda:0` or `0`). Allows users to select between CPU, a specific GPU, or other compute devices for model execution. |
| `batch` | `int` | `1` | Specifies the batch size for inference (only works when the source is [a directory, video file or `.txt` file](/modes/predict.md/#inference-sources)). A larger batch size can provide higher throughput, shortening the total amount of time required for inference. |
| `max_det` | `int` | `300` | Maximum number of detections allowed per image. Limits the total number of objects the model can detect in a single inference, preventing excessive outputs in dense scenes. |
| `vid_stride` | `int` | `1` | Frame stride for video inputs. Allows skipping frames in videos to speed up processing at the cost of temporal resolution. A value of 1 processes every frame, higher values skip frames. |
| `stream_buffer` | `bool` | `False` | Determines whether to queue incoming frames for video streams. If `False`, old frames get dropped to accomodate new frames (optimized for real-time applications). If `True', queues new frames in a buffer, ensuring no frames get skipped, but will cause latency if inference FPS is lower than stream FPS. |
| `visualize` | `bool` | `False` | Activates visualization of model features during inference, providing insights into what the model is "seeing". Useful for debugging and model interpretation. |
| `augment` | `bool` | `False` | Enables test-time augmentation (TTA) for predictions, potentially improving detection robustness at the cost of inference speed. |
| `agnostic_nms` | `bool` | `False` | Enables class-agnostic Non-Maximum Suppression (NMS), which merges overlapping boxes of different classes. Useful in multi-class detection scenarios where class overlap is common. |
| `classes` | `list[int]` | `None` | Filters predictions to a set of class IDs. Only detections belonging to the specified classes will be returned. Useful for focusing on relevant objects in multi-class detection tasks. |
| `retina_masks` | `bool` | `False` | Returns high-resolution segmentation masks. The returned masks (`masks.data`) will match the original image size if enabled. If disabled, they have the image size used during inference. |
| `embed` | `list[int]` | `None` | Specifies the layers from which to extract feature vectors or [embeddings](https://www.ultralytics.com/glossary/embeddings). Useful for downstream tasks like clustering or similarity search. |
| `project` | `str` | `None` | Name of the project directory where prediction outputs are saved if `save` is enabled. |
| `name` | `str` | `None` | Name of the prediction run. Used for creating a subdirectory within the project folder, where prediction outputs are stored if `save` is enabled. |
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