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ultralytics 8.0.164 new StreamLoader stream_buffer argument (#4596)

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Co-authored-by: jgoo9410 <jjoohhnnggooddwwiinn@gmail.com>
Co-authored-by: John Goodwin <johnf4g@gmail.com>
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@ -54,21 +54,21 @@ YOLOv8 can process different types of input sources for inference, as shown in t
Use `stream=True` for processing long videos or large datasets to efficiently manage memory. When `stream=False`, the results for all frames or data points are stored in memory, which can quickly add up and cause out-of-memory errors for large inputs. In contrast, `stream=True` utilizes a generator, which only keeps the results of the current frame or data point in memory, significantly reducing memory consumption and preventing out-of-memory issues.
| Source | Argument | Type | Notes |
|---------------|--------------------------------------------|-----------------|---------------------------------------------------------------------------------------------|
| image | `'image.jpg'` | `str` or `Path` | Single image file. |
| URL | `'https://ultralytics.com/images/bus.jpg'` | `str` | URL to an image. |
| screenshot | `'screen'` | `str` | Capture a screenshot. |
| PIL | `Image.open('im.jpg')` | `PIL.Image` | HWC format with RGB channels. |
| OpenCV | `cv2.imread('im.jpg')` | `np.ndarray` | HWC format with BGR channels `uint8 (0-255)`. |
| numpy | `np.zeros((640,1280,3))` | `np.ndarray` | HWC format with BGR channels `uint8 (0-255)`. |
| torch | `torch.zeros(16,3,320,640)` | `torch.Tensor` | BCHW format with RGB channels `float32 (0.0-1.0)`. |
| CSV | `'sources.csv'` | `str` or `Path` | CSV file containing paths to images, videos, or directories. |
| video ✅ | `'video.mp4'` | `str` or `Path` | Video file in formats like MP4, AVI, etc. |
| directory ✅ | `'path/'` | `str` or `Path` | Path to a directory containing images or videos. |
| glob ✅ | `'path/*.jpg'` | `str` | Glob pattern to match multiple files. Use the `*` character as a wildcard. |
| YouTube ✅ | `'https://youtu.be/Zgi9g1ksQHc'` | `str` | URL to a YouTube video. |
| stream ✅ | `'rtsp://example.com/media.mp4'` | `str` | URL for streaming protocols such as RTSP, RTMP, or an IP address. |
| Source | Argument | Type | Notes |
|----------------|--------------------------------------------|-----------------|---------------------------------------------------------------------------------------------|
| image | `'image.jpg'` | `str` or `Path` | Single image file. |
| URL | `'https://ultralytics.com/images/bus.jpg'` | `str` | URL to an image. |
| screenshot | `'screen'` | `str` | Capture a screenshot. |
| PIL | `Image.open('im.jpg')` | `PIL.Image` | HWC format with RGB channels. |
| OpenCV | `cv2.imread('im.jpg')` | `np.ndarray` | HWC format with BGR channels `uint8 (0-255)`. |
| numpy | `np.zeros((640,1280,3))` | `np.ndarray` | HWC format with BGR channels `uint8 (0-255)`. |
| torch | `torch.zeros(16,3,320,640)` | `torch.Tensor` | BCHW format with RGB channels `float32 (0.0-1.0)`. |
| CSV | `'sources.csv'` | `str` or `Path` | CSV file containing paths to images, videos, or directories. |
| video ✅ | `'video.mp4'` | `str` or `Path` | Video file in formats like MP4, AVI, etc. |
| directory ✅ | `'path/'` | `str` or `Path` | Path to a directory containing images or videos. |
| glob ✅ | `'path/*.jpg'` | `str` | Glob pattern to match multiple files. Use the `*` character as a wildcard. |
| YouTube ✅ | `'https://youtu.be/Zgi9g1ksQHc'` | `str` | URL to a YouTube video. |
| stream ✅ | `'rtsp://example.com/media.mp4'` | `str` | URL for streaming protocols such as RTSP, RTMP, or an IP address. |
| multi-stream ✅ | `'list.streams'` | `str` or `Path` | `*.streams` text file with one stream URL per row, i.e. 8 streams will run at batch-size 8. |
Below are code examples for using each source type:
@ -299,30 +299,31 @@ Below are code examples for using each source type:
All supported arguments:
| Name | Type | Default | Description |
|----------------|----------------|------------------------|--------------------------------------------------------------------------------|
| `source` | `str` | `'ultralytics/assets'` | source directory for images or videos |
| `conf` | `float` | `0.25` | object confidence threshold for detection |
| `iou` | `float` | `0.7` | intersection over union (IoU) threshold for NMS |
| `imgsz` | `int or tuple` | `640` | image size as scalar or (h, w) list, i.e. (640, 480) |
| `half` | `bool` | `False` | use half precision (FP16) |
| `device` | `None or str` | `None` | device to run on, i.e. cuda device=0/1/2/3 or device=cpu |
| `show` | `bool` | `False` | show results if possible |
| `save` | `bool` | `False` | save images with results |
| `save_txt` | `bool` | `False` | save results as .txt file |
| `save_conf` | `bool` | `False` | save results with confidence scores |
| `save_crop` | `bool` | `False` | save cropped images with results |
| `hide_labels` | `bool` | `False` | hide labels |
| `hide_conf` | `bool` | `False` | hide confidence scores |
| `max_det` | `int` | `300` | maximum number of detections per image |
| `vid_stride` | `bool` | `False` | video frame-rate stride |
| `line_width` | `None or int` | `None` | The line width of the bounding boxes. If None, it is scaled to the image size. |
| `visualize` | `bool` | `False` | visualize model features |
| `augment` | `bool` | `False` | apply image augmentation to prediction sources |
| `agnostic_nms` | `bool` | `False` | class-agnostic NMS |
| `retina_masks` | `bool` | `False` | use high-resolution segmentation masks |
| `classes` | `None or list` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] |
| `boxes` | `bool` | `True` | Show boxes in segmentation predictions |
| Name | Type | Default | Description |
|-----------------|----------------|------------------------|--------------------------------------------------------------------------------|
| `source` | `str` | `'ultralytics/assets'` | source directory for images or videos |
| `conf` | `float` | `0.25` | object confidence threshold for detection |
| `iou` | `float` | `0.7` | intersection over union (IoU) threshold for NMS |
| `imgsz` | `int or tuple` | `640` | image size as scalar or (h, w) list, i.e. (640, 480) |
| `half` | `bool` | `False` | use half precision (FP16) |
| `device` | `None or str` | `None` | device to run on, i.e. cuda device=0/1/2/3 or device=cpu |
| `show` | `bool` | `False` | show results if possible |
| `save` | `bool` | `False` | save images with results |
| `save_txt` | `bool` | `False` | save results as .txt file |
| `save_conf` | `bool` | `False` | save results with confidence scores |
| `save_crop` | `bool` | `False` | save cropped images with results |
| `hide_labels` | `bool` | `False` | hide labels |
| `hide_conf` | `bool` | `False` | hide confidence scores |
| `max_det` | `int` | `300` | maximum number of detections per image |
| `vid_stride` | `bool` | `False` | video frame-rate stride |
| `stream_buffer` | `bool` | `False` | buffer all streaming frames (True) or return the most recent frame (False) |
| `line_width` | `None or int` | `None` | The line width of the bounding boxes. If None, it is scaled to the image size. |
| `visualize` | `bool` | `False` | visualize model features |
| `augment` | `bool` | `False` | apply image augmentation to prediction sources |
| `agnostic_nms` | `bool` | `False` | class-agnostic NMS |
| `retina_masks` | `bool` | `False` | use high-resolution segmentation masks |
| `classes` | `None or list` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] |
| `boxes` | `bool` | `True` | Show boxes in segmentation predictions |
## Image and Video Formats